###### Monte Carlo Method

In statistics, a technique for numerically approximating the solution of a mathematical problem by studying the distribution of some random variable, often generated by a computer. The name alludes to the randomness characteristic of the games of chance played at the gambling casinos in Monte Carlo. (From Random House Unabridged Dictionary, 2d ed, 1993)

###### Markov Chains

###### Computer Simulation

###### Bayes Theorem

A theorem in probability theory named for Thomas Bayes (1702-1761). In epidemiology, it is used to obtain the probability of disease in a group of people with some characteristic on the basis of the overall rate of that disease and of the likelihood of that characteristic in healthy and diseased individuals. The most familiar application is in clinical decision analysis where it is used for estimating the probability of a particular diagnosis given the appearance of some symptoms or test result.

###### Radiometry

###### Algorithms

###### Models, Statistical

###### Photons

###### Phantoms, Imaging

Devices or objects in various imaging techniques used to visualize or enhance visualization by simulating conditions encountered in the procedure. Phantoms are used very often in procedures employing or measuring x-irradiation or radioactive material to evaluate performance. Phantoms often have properties similar to human tissue. Water demonstrates absorbing properties similar to normal tissue, hence water-filled phantoms are used to map radiation levels. Phantoms are used also as teaching aids to simulate real conditions with x-ray or ultrasonic machines. (From Iturralde, Dictionary and Handbook of Nuclear Medicine and Clinical Imaging, 1990)

###### Radiotherapy Planning, Computer-Assisted

###### Models, Genetic

###### Models, Biological

###### Scattering, Radiation

###### Likelihood Functions

###### Models, Theoretical

###### Software

###### Models, Chemical

###### Stochastic Processes

###### Reproducibility of Results

The statistical reproducibility of measurements (often in a clinical context), including the testing of instrumentation or techniques to obtain reproducible results. The concept includes reproducibility of physiological measurements, which may be used to develop rules to assess probability or prognosis, or response to a stimulus; reproducibility of occurrence of a condition; and reproducibility of experimental results.

###### Thermodynamics

A rigorously mathematical analysis of energy relationships (heat, work, temperature, and equilibrium). It describes systems whose states are determined by thermal parameters, such as temperature, in addition to mechanical and electromagnetic parameters. (From Hawley's Condensed Chemical Dictionary, 12th ed)

###### Models, Molecular

###### Protein Conformation

The characteristic 3-dimensional shape of a protein, including the secondary, supersecondary (motifs), tertiary (domains) and quaternary structure of the peptide chain. PROTEIN STRUCTURE, QUATERNARY describes the conformation assumed by multimeric proteins (aggregates of more than one polypeptide chain).

###### Radiation Dosage

The amount of radiation energy that is deposited in a unit mass of material, such as tissues of plants or animal. In RADIOTHERAPY, radiation dosage is expressed in gray units (Gy). In RADIOLOGIC HEALTH, the dosage is expressed by the product of absorbed dose (Gy) and quality factor (a function of linear energy transfer), and is called radiation dose equivalent in sievert units (Sv).

###### Genetic Markers

###### Evolution, Molecular

###### Chromosome Mapping

###### Fourier Analysis

Analysis based on the mathematical function first formulated by Jean-Baptiste-Joseph Fourier in 1807. The function, known as the Fourier transform, describes the sinusoidal pattern of any fluctuating pattern in the physical world in terms of its amplitude and its phase. It has broad applications in biomedicine, e.g., analysis of the x-ray crystallography data pivotal in identifying the double helical nature of DNA and in analysis of other molecules, including viruses, and the modified back-projection algorithm universally used in computerized tomography imaging, etc. (From Segen, The Dictionary of Modern Medicine, 1992)

###### Electron Transport

## Simplified methods for pKa and acid pH-dependent stability estimation in proteins: removing dielectric and counterion boundaries. (1/4146)

Much computational research aimed at understanding ionizable group interactions in proteins has focused on numerical solutions of the Poisson-Boltzmann (PB) equation, incorporating protein exclusion zones for solvent and counterions in a continuum model. Poor agreement with measured pKas and pH-dependent stabilities for a (protein, solvent) relative dielectric boundary of (4,80) has lead to the adoption of an intermediate (20,80) boundary. It is now shown that a simple Debye-Huckel (DH) calculation, removing both the low dielectric and counterion exclusion regions associated with protein, is equally effective in general pKa calculations. However, a broad-based discrepancy to measured pH-dependent stabilities is maintained in the absence of ionizable group interactions in the unfolded state. A simple model is introduced for these interactions, with a significantly improved match to experiment that suggests a potential utility in predicting and analyzing the acid pH-dependence of protein stability. The methods are applied to the relative pH-dependent stabilities of the pore-forming domains of colicins A and N. The results relate generally to the well-known preponderance of surface ionizable groups with solvent-mediated interactions. Although numerical PB solutions do not currently have a significant advantage for overall pKa estimations, development based on consideration of microscopic solvation energetics in tandem with the continuum model could combine the large deltapKas of a subset of ionizable groups with the overall robustness of the DH model. (+info)## Temporal and multiple quantitative trait loci analyses of resistance to bacterial wilt in tomato permit the resolution of linked loci. (2/4146)

Ralstonia solanacearum is a soil-borne bacterium that causes the serious disease known as bacterial wilt in many plant species. In tomato, several QTL controlling resistance have been found, but in different studies, markers spanning a large region of chromosome 6 showed strong association with the resistance. By using two different approaches to analyze the data from a field test F3 population, we show that at least two separate loci approximately 30 cM apart on this chromosome are most likely involved in the resistance. First, a temporal analysis of the progression of symptoms reveals a distal locus early in the development of the disease. As the disease progresses, the maximum LOD peak observed shifts toward the proximal end of the chromosome, obscuring the distal locus. Second, although classical interval mapping could only detect the presence of one locus, a statistical "two-QTL model" test, specifically adapted for the resolution of linked QTL, strongly supported the hypothesis for the presence of two loci. These results are discussed in the context of current molecular knowledge about disease resistance genes on chromosome 6 and observations made by tomato breeders during the production of bacterial wilt-resistant varieties. (+info)## Local control models of cardiac excitation-contraction coupling. A possible role for allosteric interactions between ryanodine receptors. (3/4146)

In cardiac muscle, release of activator calcium from the sarcoplasmic reticulum occurs by calcium- induced calcium release through ryanodine receptors (RyRs), which are clustered in a dense, regular, two-dimensional lattice array at the diad junction. We simulated numerically the stochastic dynamics of RyRs and L-type sarcolemmal calcium channels interacting via calcium nano-domains in the junctional cleft. Four putative RyR gating schemes based on single-channel measurements in lipid bilayers all failed to give stable excitation-contraction coupling, due either to insufficiently strong inactivation to terminate locally regenerative calcium-induced calcium release or insufficient cooperativity to discriminate against RyR activation by background calcium. If the ryanodine receptor was represented, instead, by a phenomenological four-state gating scheme, with channel opening resulting from simultaneous binding of two Ca2+ ions, and either calcium-dependent or activation-linked inactivation, the simulations gave a good semiquantitative accounting for the macroscopic features of excitation-contraction coupling. It was possible to restore stability to a model based on a bilayer-derived gating scheme, by introducing allosteric interactions between nearest-neighbor RyRs so as to stabilize the inactivated state and produce cooperativity among calcium binding sites on different RyRs. Such allosteric coupling between RyRs may be a function of the foot process and lattice array, explaining their conservation during evolution. (+info)## Quantal amplitude and quantal variance of strontium-induced asynchronous EPSCs in rat dentate granule neurons. (4/4146)

1. Excitatory postsynaptic currents (EPSCs) were recorded from granule cells of the dentate gyrus in acute slices of 17- to 21-day-old rats (22-25 C) using tissue cuts and minimal extracellular stimulation to selectively activate a small number of synaptic contacts. 2. Adding millimolar Sr2+ to the external solution produced asynchronous EPSCs (aEPSCs) lasting for several hundred milliseconds after the stimulus. Minimally stimulated aEPSCs resembled miniature EPSCs (mEPSCs) recorded in the same cell but differed from them in ways expected from the greater range of dendritic filtering experienced by mEPSCs. aEPSCs had the same stimulus threshold as the synchronous EPSCs (sEPSCs) that followed the stimulus with a brief latency. aEPSCs following stimulation of distal inputs had a slower mean rise time than those following stimulation of proximal inputs. These results suggest that aEPSCs arose from the same synapses that generated sEPSCs. 3. Proximally elicited aEPSCs had a mean amplitude of 6.7 +/- 2.2 pA (+/- s.d., n = 23 cells) at -70 mV and an amplitude coefficient of variation of 0. 46 +/- 0.08. 4. The amplitude distributions of sEPSCs never exhibited distinct peaks. 5. Monte Carlo modelling of the shapes of aEPSC amplitude distributions indicated that our data were best explained by an intrasite model of quantal variance. 6. It is concluded that Sr2+-evoked aEPSCs are uniquantal events arising at synaptic terminals that were recently invaded by an action potential, and so provide direct information about the quantal amplitude and quantal variance at those terminals. The large quantal variance obscures quantization of the amplitudes of evoked sEPSCs at this class of excitatory synapse. (+info)## Bayesian inference on biopolymer models. (5/4146)

MOTIVATION: Most existing bioinformatics methods are limited to making point estimates of one variable, e.g. the optimal alignment, with fixed input values for all other variables, e.g. gap penalties and scoring matrices. While the requirement to specify parameters remains one of the more vexing issues in bioinformatics, it is a reflection of a larger issue: the need to broaden the view on statistical inference in bioinformatics. RESULTS: The assignment of probabilities for all possible values of all unknown variables in a problem in the form of a posterior distribution is the goal of Bayesian inference. Here we show how this goal can be achieved for most bioinformatics methods that use dynamic programming. Specifically, a tutorial style description of a Bayesian inference procedure for segmentation of a sequence based on the heterogeneity in its composition is given. In addition, full Bayesian inference algorithms for sequence alignment are described. AVAILABILITY: Software and a set of transparencies for a tutorial describing these ideas are available at http://www.wadsworth.org/res&res/bioinfo/ (+info)## A hierarchical approach to protein molecular evolution. (6/4146)

Biological diversity has evolved despite the essentially infinite complexity of protein sequence space. We present a hierarchical approach to the efficient searching of this space and quantify the evolutionary potential of our approach with Monte Carlo simulations. These simulations demonstrate that nonhomologous juxtaposition of encoded structure is the rate-limiting step in the production of new tertiary protein folds. Nonhomologous "swapping" of low-energy secondary structures increased the binding constant of a simulated protein by approximately 10(7) relative to base substitution alone. Applications of our approach include the generation of new protein folds and modeling the molecular evolution of disease. (+info)## The topomer-sampling model of protein folding. (7/4146)

Clearly, a protein cannot sample all of its conformations (e.g., approximately 3(100) approximately 10(48) for a 100 residue protein) on an in vivo folding timescale (<1 s). To investigate how the conformational dynamics of a protein can accommodate subsecond folding time scales, we introduce the concept of the native topomer, which is the set of all structures similar to the native structure (obtainable from the native structure through local backbone coordinate transformations that do not disrupt the covalent bonding of the peptide backbone). We have developed a computational procedure for estimating the number of distinct topomers required to span all conformations (compact and semicompact) for a polypeptide of a given length. For 100 residues, we find approximately 3 x 10(7) distinct topomers. Based on the distance calculated between different topomers, we estimate that a 100-residue polypeptide diffusively samples one topomer every approximately 3 ns. Hence, a 100-residue protein can find its native topomer by random sampling in just approximately 100 ms. These results suggest that subsecond folding of modest-sized, single-domain proteins can be accomplished by a two-stage process of (i) topomer diffusion: random, diffusive sampling of the 3 x 10(7) distinct topomers to find the native topomer ( approximately 0.1 s), followed by (ii) intratopomer ordering: nonrandom, local conformational rearrangements within the native topomer to settle into the precise native state. (+info)## Testing the fit of a quantal model of neurotransmission. (8/4146)

Many studies of synaptic transmission have assumed a parametric model to estimate the mean quantal content and size or the effect upon them of manipulations such as the induction of long-term potentiation. Classical tests of fit usually assume that model parameters have been selected independently of the data. Therefore, their use is problematic after parameters have been estimated. We hypothesized that Monte Carlo (MC) simulations of a quantal model could provide a table of parameter-independent critical values with which to test the fit after parameter estimation, emulating Lilliefors's tests. However, when we tested this hypothesis within a conventional quantal model, the empirical distributions of two conventional goodness-of-fit statistics were affected by the values of the quantal parameters, falsifying the hypothesis. Notably, the tests' critical values increased when the combined variances of the noise and quantal-size distributions were reduced, increasing the distinctness of quantal peaks. Our results support two conclusions. First, tests that use a predetermined critical value to assess the fit of a quantal model after parameter estimation may operate at a differing unknown level of significance for each experiment. Second, a MC test enables a valid assessment of the fit of a quantal model after parameter estimation. (+info)###### Monte Carlo simulation of xenon adsorption with dealumination of an idealized mordenite structure<...

###### Performance of Hamiltonian Monte Carlo and No-U-Turn Sampler for estimating genetic parameters and breeding values | Genetics...

###### Self-evolving atomistic kinetic Monte Carlo simulations of defects in materials (Journal Article) | DOE PAGES

###### Markov Chain Monte Carlo Method without Detailed Balance - Condensed Matter > Statistical Mechanics - pdf...

###### Monte Carlo simulation of the transient response of single photon absorption in X-ray pixel detectors

###### Evaluation based on Monte Carlo simulation of lifetime attributable risk of cancer after neck X-ray radiography - Fingerprint ...

###### talks.cam : From calcium imaging to spikes, using sequential Monte Carlo methods

###### First Passage Probability Estimation of Wind Turbines by Markov Chain Monte Carlo - Danish National Research Database-Den...

###### NOPR: Estimation of uncertainty of effective area of a pneumatic pressure reference standard using Monte Carlo method

###### Dose Assessment of Eye and Its Components in Proton Therapy by Monte Carlo Method

###### Monte Carlo Method to Solve Diffusion Equation and Error Analysis | Journal of Nepal Mathematical Society

###### Download Introducing Monte Carlo Methods With R

###### Particle flow for sequential Monte Carlo implementation of probability hypothesis density - Surrey Research Insight Open Access

###### Monte Carlo algorithm - Simple English Wikipedia, the free encyclopedia

###### Adsorption equilibrium of polar/non-polar mixtures on MCM-41: Experiments and Monte Carlo simulation<...

###### Monte Carlo method - Wikipedia

###### The Price is Right : Project valuation for Project Portfolio Management using Markov Chain Monte Carlo Simulation

###### Implementation and Analysis of an Adaptive Multilevel Monte Carlo Algorithm

###### Free Monte Carlo Simulations Download

###### Alexander Shkolnik, CRMR Postdoctoral Scholar, to give contributed session at the International Conference on Monte Carlo...

###### History-by-History Variance in Monte Carlo Simulation of Radiation Interactions with Matter

###### Implementation and validation of an add-on MLC for Monte Carlo dose calculations in conformal stereotactic radiosurgery

###### A Monte Carlo Analysis of Technical Inefficiency Predictors

###### Simulation of Electron Transport in InGaAs/AlGaAs HEMTs Using an Electrothermal Monte Carlo Method<...

###### 0811.4375] Off-Lattice Self-Learning Kinetic Monte Carlo: Application to 2D Cluster Diffusion on the fcc(111) Surface

###### Incorporation of multivariate statistical distribution of magnitude-distance and Monte-Carlo simulation in probabilistic...

###### Scale property Monte Carlo driven inversion of surface wave data | Earthdoc

###### A Monte Carlo approach to describe the reduction profiles of bidimensional MoOx structures grown on an alumina sustrate

###### Advanced Analytic Techniques: Summary of Findings: Monte Carlo Simulations (3.5 out of 5 Stars)

###### AES E-Library » Restoration of Nonlinearly Distorted Audio Using Markov Chain Monte Carlo Methods

###### How many operating rooms are needed to manage non-elective surgical cases? A Monte Carlo simulation study | BMC Health Services...

###### Reversible jump MCMC for volumetric calibration. - Lancaster EPrints

###### Rao-Blackwellization of Particle Markov Chain Monte Carlo Methods Using Forward Filtering Backward Sampling - IEEE Journals &...

###### Radyalis Releases Next-Generation Monte Carlo Proton Therapy Planning | Imaging Technology News

###### Perform Monte Carlo simulation

###### Thermodynamics of L10 ordering in FePt nanoparticles studied by Monte Carlo simulations based on an analytic bond-order...

###### An Explanation of Signal Changes in DW-fMRI: Monte Carlo Simulation Study of Restricted Diffusion of Water Molecules Using 3D...

###### Random vibration Monte Carlo simulation using multiple harmonic function schemes on Environmental XPRT

###### Image Analysis, Random Fields and Dynamic Monte Carlo Methods: A Mathematical Introduction by Gerhard Winkler, Paperback |...

###### Simulating a diffusion on a graph. Application to reservoir engineering : Monte Carlo Methods and Applications mcma

###### Selective hydrogen production at Pt(111) investigated by Quantum Monte Carlo methods for metal catalysis - Tampere University...

###### Introduction To Monte Carlo Methods - alexhwoods

###### Ebook Monte Carlo Methods In Quantum Problems

###### Monte Carlo method - Find link

###### Scratch Programming: The Area of Texas Using the Monte Carlo Method

###### Monte Carlo methods for fissured porous media: a gridless approach - pdf descargar

###### Monte Carlo simulation of OLS and linear mixed model inference of phenotypic effects on gene expression [PeerJ]

###### Particle Gibbs Split-Merge Sampling for Bayesian Inference in Mixture Models

###### Study of the ST2 model of water close to the liquid-liquid critical point - Physical Chemistry Chemical Physics (RSC Publishing)

###### Advances in Quantum Monte Carlo - James B. Anderson; Stuart M. Rothstein - Oxford University Press

**Monte** **Carlo** **method**

Mathematics portal Auxiliary field

**Monte****Carlo**Biology**Monte****Carlo****method**Direct simulation**Monte****Carlo**Dynamic**Monte****Carlo**... for**Monte****Carlo**molecular modeling Mean-field particle**methods****Monte****Carlo****method**for photon transport**Monte****Carlo****methods**for ... electron transport**Monte****Carlo**N-Particle Transport Code Morris**method**Multilevel**Monte****Carlo****method**Quasi-**Monte****Carlo****method**... a**Monte****Carlo****method**, and a**Monte****Carlo**simulation: a simulation is a fictitious representation of reality, a**Monte****Carlo**...###### Quasi-**Monte** **Carlo** **method**

**Monte**

**Carlo**

**method**

**Monte**

**Carlo**

**methods**in finance Quasi-

**Monte**

**Carlo**

**methods**in finance Biology

**Monte**

**Carlo**

**method**Computational ... on

**Monte**

**Carlo**and quasi-

**Monte**

**Carlo**

**methods**A very intuitive and comprehensive introduction to Quasi-

**Monte**

**Carlo**

**methods**(Use ... Hence, the

**Monte**

**Carlo**

**method**and the quasi-

**Monte**

**Carlo**

**method**are beneficial in these situations. The approximation error of ... Hence, in general, the accuracy of the quasi-

**Monte**

**Carlo**

**method**increases faster than that of the

**Monte**

**Carlo**

**method**. However, ...

###### Dynamic **Monte** **Carlo** **method**

In chemistry, dynamic

**Monte****Carlo**(DMC) is a**Monte****Carlo****method**for modeling the dynamic behaviors of molecules by comparing ... It is essentially the same as Kinetic**Monte****Carlo**. Unlike the Metropolis**Monte****Carlo****method**, which has been employed to study ... Large-scale systems are able to be calculated by this**method**. Hybrid**Monte****Carlo**(Meng and Weinberg 1994): B. Meng and W. H. ... v t e (**Monte****Carlo****methods**, Computational chemistry, All stub articles, Chemistry stubs, Computational science stubs). ...###### Multilevel **Monte** **Carlo** **method**

... and the combination of MLMC with the Quasi-

**Monte****Carlo****method**.**Monte****Carlo****method****Monte****Carlo****methods**in finance Quasi-**Monte**... is then approximated by a**Monte****Carlo****method**, resulting in the multilevel**Monte****Carlo****method**. Note that taking a sample of the ... end until converged Recent extensions of the multilevel**Monte****Carlo****method**include multi-index**Monte****Carlo**, where more than one ... MLMC**methods**can greatly reduce the computational cost of standard**Monte****Carlo****methods**by taking most samples with a low ...###### Biology **Monte** **Carlo** **method**

Biology

**Monte****Carlo****methods**(BioMOCA) have been developed at the University of Illinois at Urbana-Champaign to simulate ion ... namely the Boltzmann transport**Monte****Carlo**(BTMC) and particle-particle-particle-mesh (P3M). The first one uses**Monte****Carlo**...**Monte****Carlo****method**Biology Computational biology van der Straaten, T.A.; Kathawala, G.; Trellakis, A.; Eisenberg §, R.S.; ... C. Jacoboni, P. Lugli, The**Monte****Carlo****Method**for Semiconductor Device Simulation, Springer Verlag, New York (1989) R. Hockney ...**Monte** **Carlo** **methods** in finance

**Monte**

**Carlo**

**methods**are ideally suited to evaluating difficult integrals (see also

**Monte**

**Carlo**

**method**). Thus if we suppose that ... Quasi-

**Monte**

**Carlo**

**methods**in finance

**Monte**

**Carlo**

**method**Historical simulation (finance) Stock market simulator Real options ...

**Monte**

**Carlo**:methodologies and applications for pricing and risk management. Risk. Paul Glasserman (2003).

**Monte**

**Carlo**

**methods**... General

**Monte**

**Carlo**Simulation (Encyclopedia of Quantitative Finance), Peter Jaeckel and Eckhard Plateny

**Monte**

**Carlo**

**Method**, ...

**Monte** **Carlo** **method** in statistical physics

**Monte**

**Carlo**integration Metropolis algorithm Importance sampling Quantum

**Monte**

**Carlo**

**Monte**

**Carlo**molecular modeling Allen, M.P ...

**Monte**

**Carlo**in statistical physics refers to the application of the

**Monte**

**Carlo**

**method**to problems in statistical physics, or ... For those systems, the

**Monte**

**Carlo**integration (and not to be confused with

**Monte**

**Carlo**

**method**, which is used to simulate ... The general motivation to use the

**Monte**

**Carlo**

**method**in statistical physics is to evaluate a multivariable integral. The ...

**Monte** **Carlo** **methods** for option pricing

**Monte**

**Carlo**

**methods**in finance Quasi-

**Monte**

**Carlo**

**methods**in finance Stochastic modelling (insurance) Stochastic asset model ... In mathematical finance, a

**Monte**

**Carlo**option model uses

**Monte**

**Carlo**

**methods**to calculate the value of an option with multiple ...

**Monte**

**Carlo**

**methods**in finance. John Wiley and Sons. ISBN 978-0-471-49741-7. Don L. McLeish (2005).

**Monte**

**Carlo**Simulation & ...

**Monte**

**Carlo**Statistical

**Methods**. ISBN 978-0-387-21239-5. Online tools

**Monte**

**Carlo**simulated stock price time series and random ...

###### Quasi-**Monte** **Carlo** **methods** in finance

The quasi-

**Monte****Carlo**(QMC)**method**is defined by φ Q M C ( f ) = 1 n ∑ i = 1 n f ( x i ) , {\displaystyle \varphi ^{\mathop {\ ... To break this curse of dimensionality one can use the**Monte****Carlo**(MC)**method**defined by φ M C ( f ) = 1 n ∑ i = 1 n f ( x i ... The standard terminology quasi-**Monte****Carlo**is somewhat unfortunate since MC is a randomized**method**whereas QMC is purely ... It is well known that the expected error of**Monte****Carlo**is of order n − 1 / 2 {\displaystyle n^{-1/2}} . Thus, the cost of the ...**Monte** **Carlo** **method** for photon transport

This flexibility makes

**Monte****Carlo**modeling a powerful tool. Thus, while computationally inefficient,**Monte****Carlo****methods**are ... in biological tissue**Monte****Carlo****method**Convolution for optical broad-beam responses in scattering media**Monte****Carlo****methods**... Sweden GPU acceleration of**Monte****Carlo**simulations and scalable**Monte****Carlo**. Open source code for download. Cloud-based**Monte**... Due to the nature of PDT, it is useful to use**Monte****Carlo****methods**for modeling scattering and absorption in the tissue in order ...**Monte** **Carlo** **methods** for electron transport

**Monte**

**Carlo**

**method**Semiconductor device

**Monte**

**Carlo**

**method**for photon transport Band structure

**Method**of quantum ... characteristics Quantum

**Monte**

**Carlo**Quasi-

**Monte**

**Carlo**

**method**Karl Hess, ed. (1991).

**Monte**

**Carlo**Device Simulation: Full Band ... The

**Monte**

**Carlo**

**method**for electron transport is a semiclassical

**Monte**

**Carlo**(MC) approach of modeling semiconductor transport ... whereas the

**Monte**

**Carlo**is the stochastic approach used to solve the BTE. The semiclassical

**Monte**

**Carlo**

**method**is a statistical ...

**Monte** **Carlo** tree search

Rémi Coulom described the application of the

**Monte****Carlo****method**to game-tree search and coined the name**Monte****Carlo**tree search ... the basic version of**Monte****Carlo**tree search converges only in so called "**Monte****Carlo**Perfect" games. However,**Monte****Carlo**tree ...**Monte****Carlo**) trees and was the main seed for UCT.) Although it has been proven that the evaluation of moves in**Monte****Carlo**tree ... There are automated**methods**to tune the parameters to maximize the win rate.**Monte****Carlo**tree search can be concurrently ...###### Path integral **Monte** **Carlo**

... (PIMC) is a quantum

**Monte****Carlo****method**used to solve quantum statistical mechanics problems ... As with all**Monte****Carlo****method**based approaches, a large number of points must be calculated. In principle, as more path ... The application of**Monte****Carlo****methods**to path integral simulations of condensed matter systems was first pursued in a key ... Freeman, David L; Doll, J. D (1994). "Fourier path integral**Monte****Carlo****method**for the calculation of the microcanonical ...###### Hamiltonian **Monte** **Carlo**

... from scratch Optimization and

**Monte****Carlo****Methods**(**Monte****Carlo****methods**, Markov chain**Monte****Carlo**). ... The Hamiltonian**Monte****Carlo**algorithm (originally known as hybrid**Monte****Carlo**) is a Markov chain**Monte****Carlo****method**for ... Dynamic**Monte****Carlo****method**Software for**Monte****Carlo**molecular modeling Stan Metropolis-adjusted Langevin algorithm Duane, Simon ... Barbu, Adrian; Zhu, Song-Chun (2020). "Hamiltonian and Langevin**Monte****Carlo**".**Monte****Carlo****Methods**. Singapore: Springer. pp. 281 ...###### Markov chain **Monte** **Carlo**

Random walk

**Monte****Carlo****methods**are a kind of random simulation or**Monte****Carlo****method**. However, whereas the random samples of ... Atzberger, P. "An Introduction to**Monte**-**Carlo****Methods**" (PDF). Berg, Bernd A. (2004). Markov Chain**Monte****Carlo**Simulations and ... Simulation and the**Monte****Carlo****Method**(2nd ed.). Wiley. ISBN 978-0-470-17794-5. Smith, R.L. (1984). "Efficient**Monte****Carlo**... Markov chain**Monte****Carlo**,**Monte****Carlo****methods**, Computational statistics, Markov models, Bayesian estimation). ...###### Continuous-time quantum **Monte** **Carlo**

To distinguish it from other

**Monte****Carlo****methods**for such systems that also work in continuous time, the**method**is then usually ... Rubtsov, A.N.; Savkin, V.V.; Lichtenstein, A.I. (2005). "Continuous-time quantum**Monte****Carlo****method**for fermions". Phys. Rev. B ... The attribute continuous-time was introduced to distinguish the**method**from the then-predominant Hirsch-Fye quantum**Monte****Carlo**... Assaad, F.F.; Lang, T.C. (2007). "Diagrammatic determinantal quantum**Monte****Carlo****methods**: Projective schemes and applications ...**Monte** **Carlo** algorithm

**Monte**

**Carlo**

**methods**, algorithms used in physical simulation and computational statistics based on taking random samples ... The term "

**Monte**

**Carlo**" was first introduced in 1947 by Nicholas Metropolis. Las Vegas algorithms are a dual of

**Monte**

**Carlo**... Metropolis, N. (1987). "The beginning of the

**Monte**

**Carlo**

**method**" (PDF). Los Alamos Science (1987 Special Issue dedicated to ... A false-biased

**Monte**

**Carlo**algorithm is always correct when it returns false; a true-biased algorithm is always correct when it ...

**Monte** **Carlo** Casino

... a quantum

**Monte****Carlo****method**Casino, a portion of the Circuit de Monaco of the Monaco Grand Prix The Casino de**Monte**-**Carlo**main ... It includes a casino, the Opéra de**Monte**-**Carlo**, and the office of Les Ballets de**Monte**-**Carlo**. The Casino de**Monte**-**Carlo**is ... The**Monte****Carlo**Casino, officially named Casino de**Monte**-**Carlo**, is a gambling and entertainment complex located in Monaco. ... The**Monte****Carlo****method**, a computational approach which relies on repeated random sampling to solve difficult numerical problems ...###### Reptation **Monte** **Carlo**

... is a quantum

**Monte****Carlo****method**. It is similar to Diffusion**Monte****Carlo**, except that it works with paths ... In both diffusion**Monte****Carlo**and reptation**Monte****Carlo**, the**method**first aims to solve the time-dependent Schrödinger equation ... This is how diffusion**Monte****Carlo**works. Reptation**Monte****Carlo**works in a very similar way, but is focused on the paths that ... S. Baroni & S. Moroni (1999). "Reptation Quantum**Monte****Carlo**: A**Method**for Unbiased Ground-State Averages and Imaginary-Time ...###### Variational **Monte** **Carlo**

In computational physics, variational

**Monte****Carlo**(VMC) is a quantum**Monte****Carlo****method**that applies the variational**method**to ... 1984).**Monte****Carlo****Methods**in Quantum Problems. Dordrecht: Springer Netherlands. doi:10.1007/978-94-009-6384-9. ISBN 978-94-009 ... Metropolis-Hastings algorithm Rayleigh-Ritz**method**Time-dependent variational**Monte****Carlo**McMillan, W. L. (19 April 1965). " ... Following the**Monte****Carlo****method**for evaluating integrals, we can interpret , Ψ ( X , a ) , 2 ∫ , Ψ ( X , a ) , 2 d X {\ ...**Monte** **Carlo** N-Particle Transport Code

Safety code (nuclear reactor) Nuclear data

**Monte****Carlo****method****Monte****Carlo****methods**for electron transport Nuclear reactor ... The**Monte****Carlo****method**for radiation particle transport has its origins at LANL dates back to 1946. The creators of these ...**Monte****Carlo**software, Physics software, Fortran software, Scientific simulation software,**Monte****Carlo**particle physics software ...**Monte****Carlo****methods**for particle transport have been driving computational developments since the beginning of modern computers ...###### Gaussian quantum **Monte** **Carlo**

... is a quantum

**Monte****Carlo****method**that shows a potential solution to the fermion sign problem ... Corney, J. F.; Drummond, P. D. (2004-12-20). "Gaussian Quantum**Monte****Carlo****Methods**for Fermions and Bosons". Physical Review ... "Symmetry projection schemes for Gaussian**Monte****Carlo****methods**". Physical Review B. 72 (22): 224518. arXiv:cond-mat/0509149. ... Quantum**Monte****Carlo**, All stub articles, Quantum chemistry stubs). ...###### Quantum **Monte** **Carlo**

The diverse flavors of quantum

**Monte****Carlo**approaches all share the common use of the**Monte****Carlo****method**to handle the multi- ...**Monte****Carlo**Determinant quantum**Monte****Carlo**or Hirsch-Fye quantum**Monte****Carlo**Hybrid quantum**Monte****Carlo**Path integral**Monte**... World-line quantum**Monte****Carlo**Time-dependent variational**Monte****Carlo**: An extension of the variational**Monte****Carlo**to study the ... Reptation**Monte****Carlo**: Recent zero-temperature**method**related to path integral**Monte****Carlo**, with applications similar to ...###### Diffusion **Monte** **Carlo**

... (DMC) or diffusion quantum

**Monte****Carlo**is a quantum**Monte****Carlo****method**that uses a Green's function to ... P.J. Reynolds (1994).**Monte****Carlo****Methods**in Ab Initio Quantum Chemistry. World Scientific Lecture and Course Notes in ... Grimm, R.C; Storer, R.G (1971). "**Monte**-**Carlo**solution of Schrödinger's equation". Journal of Computational Physics. 7 (1): 134- ... We can do these integrals by**Monte****Carlo**integration. Reynolds, Peter J.; Tobochnik, Jan; Gould, Harvey (1990). "Diffusion ...###### Direct simulation **Monte** **Carlo**

... (DSMC)

**method**uses probabilistic**Monte****Carlo**simulation to solve the Boltzmann equation for ... Direct Simulation**Monte****Carlo****Method**: Visual Simulation Programs created by GA Bird. DSMC Demo Applet by Greg Khanlarov Course ... Currently, the DSMC**method**has been applied to the solution of flows ranging from estimation of the Space Shuttle re-entry ... The DSMC**method**has been extended to model continuum flows (Kn < 1) and the results can be compared with Navier Stokes ...**Monte** **Carlo** integration

... is a technique for numerical integration using random numbers. It is a particular

**Monte****Carlo****method**... This**method**is particularly useful for higher-dimensional integrals. There are different**methods**to perform a**Monte****Carlo**... sequential**Monte****Carlo**(also known as a particle filter), and mean-field particle**methods**. In numerical integration,**methods**... which is the promised advantage of**Monte****Carlo**integration against most deterministic**methods**that depend exponentially on the ...###### Energy-based generative neural network

Barbu, Adrian; Zhu, Song-Chun (2020).

**Monte****Carlo****Methods**. Springer. Wu, Ying Nian; Xie, Jianwen; Lu, Yang; Zhu, Song-Chun ( ... The parameter of the neural network in this model is trained in a generative manner by Markov chain**Monte****Carlo**(MCMC)-based ... the algorithm samples the synthesized examples from the current model by a gradient-based MCMC**method**, e.g., Langevin dynamics ...###### Low-discrepancy sequence

Discrepancy theory Markov chain

**Monte****Carlo**Quasi-**Monte****Carlo****method**Sparse grid Systematic sampling Beck, József (1989). "A ... this is the**Monte****Carlo****method**. If the points are chosen as elements of a low-discrepancy sequence, this is the quasi-**Monte**... Elements need not be recomputed in the random**Monte****Carlo****method**if N is increased, but the point sets do not have minimal ...**Monte****Carlo****Methods**. doi:10.1007/978-94-009-5819-7. ISBN 978-94-009-5821-0. Herman Tulleken. Tulleken, Herman (March 2008). " ...###### Non-uniform random variate generation

The first

**methods**were developed for**Monte**-**Carlo**simulations in the Manhattan project,[citation needed] published by John von ...**Monte****Carlo****Methods**. National Bureau of Standards Applied Mathematics Series. Vol. 12. US Government Printing Office. pp. 36-38 ... New York: Springer Fishman, G.S. (1996)**Monte****Carlo**. Concepts, Algorithms, and Applications. New York: Springer Hörmann, W.; J ... Alias**method**, computational time is constant, using some pre-computed tables. There are other**methods**that cost constant time. ...###### Reverse **Monte** **Carlo**

The Reverse

**Monte****Carlo**(RMC) modelling**method**is a variation of the standard Metropolis-Hastings algorithm to solve an inverse ... There are four publicly available implementations of the RMC**method**. Fundamental Library Language for Reverse**Monte****Carlo**or ... Articles with short description, Short description matches Wikidata, Use dmy dates from September 2015,**Monte****Carlo****methods**, ... Hybrid Reverse**Monte****Carlo****method**with silicon, carbon, germanium and silicon carbide potentials". Computer Physics ...###### Uncertainty quantification

Techniques such as the

**Monte****Carlo****method**are frequently used. A probability distribution can be represented by its moments (in ... Local expansion-based**methods**: Taylor series, perturbation**method**, etc. These**methods**have advantages when dealing with ...**Monte****Carlo**simulations, importance sampling, adaptive sampling, etc. General surrogate-based**methods**: In a non-instrusive ... Most probable point (MPP)-based**methods**: first-order reliability**method**(FORM) and second-order reliability**method**(SORM). ...###### Muon tomography

Tanaka, H.K.M. (2007). "

**Monte**-**Carlo**simulations of atmospheric muon production: Implication of the past martian environment". ... New**methods**of warhead imaging are of crucial importance for the success of mutual inspections. Muon Tomography can be used for ... The**method**used for this experiment could be applied to other archeological targets to check the structural integrity of ... reported using tomographic**methods**to track the passage of cosmic rays muons through cesium iodide crystals for quality control ...###### Classical fluid

... can be studied using quantum

**Monte****Carlo****methods**, Feynman path integral equation**methods**, and approximately via CHNC integral- ... equation**methods**. Bose-Einstein condensate Fermi liquid Many-body theory Quantum fluid R. Balescu, Equilibrium and ... An essentially very accurate way of determining the properties of classical fluids is provided by the**method**of molecular ...###### Markov decision process

For example, the dynamic programming algorithms described in the next section require an explicit model, and

**Monte****Carlo**tree ... Solutions for MDPs with finite state and action spaces may be found through a variety of**methods**such as dynamic programming. ... iterative**method**) This variant has the advantage that there is a definite stopping condition: when the array π {\displaystyle \ ... Lloyd Shapley's 1953 paper on stochastic games included as a special case the value iteration**method**for MDPs, but this was ...###### List of female dancers

Ballet Russe de

**Monte****Carlo**, Grand Ballet du Marquis de Cuevas, also performed on Broadway Cléo de Mérode (1875-1966), dancer, ... taught Isadora Duncan's**method**Lucie Kadlčáková (born 1982), ice dancer Daria Klimentová (born 1971), ballet dancer, former ... Ballet Russe de**Monte****Carlo**, co-founder of University of Oklahoma School of Dance Lia Cirio, dancer, principal dancer, Boston ... Ballets de**Monte**-**Carlo**Caroline Truong (born 1980), ice dancer Marie van Goethem (born 1865, death unknown), dancer, model ...###### Photon mapping

A

**Monte****Carlo****method**called Russian roulette is used to choose one of these actions. If the photon is absorbed, no new ... However, it is a consistent**method**, and the accuracy of a render can be increased by increasing the number of photons. As the ... This was the original way Jensen implemented it; however, the**method**becomes slow for highly scattering materials, and ... which means that averaging infinitely many renders of the same scene using this**method**does not converge to a correct solution ...###### Stanislaw Ulam

"The

**Monte****Carlo****method**". Metropolis and Ulam published the first unclassified paper on the**Monte****Carlo****method**in 1949. Fermi, ... The**Monte****Carlo****method**has become a ubiquitous and standard approach to computation, and the**method**has been applied to a vast ... Ulam, who was to become an originator of the**Monte****Carlo****method**and co-discoverer of the hydrogen-bomb,... used to tease me by ... The Day After Trinity at IMDb Eckhardt, Roger (1987). "Stan Ulam, John von Neumann, and the**Monte****Carlo****Method**" (PDF). Los ...###### Backgammon

In this

**method**, a**Monte**-**Carlo**evaluation of positions is conducted (typically thousands of trials) where different random dice ... The**Monte****Carlo**tournament draws hundreds of players and spectators, and is played over the course of a week. By the 21st ...**Monte****Carlo**was universally acknowledged as the site of the World Backgammon Championship and has remained as such for thirty ... 50, section 1, part 2. Maxa, Rudy (September 6, 1981). "Where the Rich And the Royal Play Their Games-**Monte****Carlo's**Seven-Day ...###### Solid hydrogen

Quantum

**Monte****Carlo****methods**together with a first-principles treatment of anharmonic vibrational effects have then been used to ... N. D. Drummond, B. Monserrat, J. H. Lloyd-Williams, P. Lopez Rios, C. J. Pickard and R. J. Needs (2015). "Quantum**Monte****Carlo**...###### Comparison of Gaussian process software

... gradient descent or Markov chain

**Monte****Carlo**. These columns are about the possibility of fitting datapoints simultaneously to a ... Ambikasaran, S.; Foreman-Mackey, D.; Greengard, L.; Hogg, D. W.; O'Neil, M. (1 Feb 2016). "Fast Direct**Methods**for Gaussian ...###### Pigeon-shooting

The popularity of pigeon shooting at

**Monte****Carlo**included creation of new types of gun stocks; the "**Monte****Carlo**" comb. Pigeon ... efforts carried out in cities where feral pigeons are considered a nuisance and are often controlled using lethal**methods**. The ... "Monaco: an extraordinary history of unusual sports".**Monte****Carlo**Legend. Archived from the original on 2020-02-21. Retrieved ... Match of Nations World Championship**Monte****Carlo**, Monaco - Prix de Larvotto and Prix Gaston Rambaud Havana, Cuba - The Pan ...###### Joseph Conrad

He achieves nothing there and, wishing to improve his finances, tries his luck in

**Monte****Carlo**and loses the 800 fr[ancs] he had ... reference points for Conrad's fragmentary**method**[of presenting information about characters and events] include Picasso and T. ...###### John Texter

... initiating

**Monte****Carlo**analyses and modeling of DNA photochemical processes, and a postdoctoral year with Eugene S. Stevens at ... as practical**method**of characterizing electrokinetics in concentrated dispersions by developing calibration**methods**to ... developing a time-dependent Hartree-Fock model for circular dichroism in saccharides and a**Monte****Carlo**-based nonlinear ...###### Electrostatic analyzer

... which includes the capability of performing

**Monte****Carlo**simulations on known test particles, thus providing the designer a ... Nuclear Instruments and**Methods**in Physics Research Section A. 500 (1-3): 62-67. Bibcode:2003NIMPA.500...62I. doi:10.1016/S0168 ...###### Causal sets

**Monte**-

**Carlo**simulations have provided evidence for a continuum phase in 2D using the Benincasa-Dowker action. Causal dynamical ... Tests in conformally-flat spacetimes have shown these two

**methods**to be accurate. An ongoing task is to develop the correct ...

###### Anita Loos

... she had seen Audrey Hepburn in a hotel lobby in

**Monte****Carlo**. Gigi opened in the fall of 1951 and would run until the spring of ... She and the ear, nose and throat specialist who was treating her came up with a**method**of fixing Emerson's hypochondria. The ... Loos devised a**method**of cobbling together published reports of Manhattan social life and mailing them to a friend in New York ...###### Nuclear power

Review of recent trends and analysis of future investments using

**Monte****Carlo**Simulation". Renewable and Sustainable Energy ... Commonly suggested**methods**to isolate LLFP waste from the biosphere include separation and transmutation, synroc treatments, or ... Nuclear power is one of the leading low carbon power generation**methods**of producing electricity, and in terms of total life- ... W Wayt Gibbs (2013-12-30). "Triple-threat**method**sparks hope for fusion". Nature. 505 (7481): 9-10. Bibcode:2014Natur.505....9G ...###### Emily A. Carter

She pioneered the combination of ab initio quantum chemistry with kinetic

**Monte****Carlo**simulations (KMC), molecular dynamics (MD ... She has also proposed**methods**for protecting materials from failure. Carter has developed fast**methods**for orbital-free density ... Early contributions included**methods**for accurate description of molecules at the quantum level and an algorithm for ... She has developed ab initio quantum chemistry**methods**and applied them to the study of materials. ...###### Pressure-temperature-time path

... a

**Monte****Carlo**assessment and implications for tectonic interpretations". Geoscience Frontiers. 7 (4): 591-607. doi:10.1016/j. ... The Gibbs**method**formalism is a**method**used to analyze pressures and temperatures of zoned minerals and textural changes in ... Both**methods**have their advantages and limitations. The XRF**method**provides a non-biased estimation, but may neglect the ... the**method**of inversely inferring the metamorphic events from rock samples via traditional petrological investigation**methods**( ...###### List of mathematics-based **methods**

Sainte-Laguë

**method**(voting systems) Schulze**method**(voting systems) Sequential**Monte****Carlo****method**Simplex**method**Spectral ...**Method**of moving frames (differential geometry)**Method**of successive substitution (number theory)**Monte****Carlo****method**( ... Adams'**method**(differential equations) Akra-Bazzi**method**(asymptotic analysis) Bisection**method**(root finding) Brent's**method**( ... Finite volume**method**(numerical analysis) Highest averages**method**(voting systems)**Method**of exhaustion**Method**of infinite ...###### Power system simulation

Another technique to model variability is the

**Monte****Carlo****method**, in which different combinations of inputs and resulting ... This**method**can be applied to simulations for system security and unit commitment risk, and it is increasingly being used to ... Other power flow solution**methods**like stochastic optimization incorporate the uncertainty found in modeling power systems by ...###### Autonomous research robot

These platforms can map buildings and navigate out-of-the-box, using SLAM and a variation on

**Monte****Carlo****method**/Markov ... This**method**creates a human readable map of the robot's workspace that can control and track robots as they move. Evolution ...###### Talladega Nights: The Ballad of Ricky Bobby

He drives the #47 Old Spice Chevrolet

**Monte****Carlo**. Reilly previously had a role in Days of Thunder. Austin Grimm as 10-year-old ... When his life hits rock bottom, Bobby's estranged father Reese returns to remind him how to drive, using unorthodox**methods**... He originally drove the #26 Laughing Clown Malt Liquor Chevrolet**Monte****Carlo**until it became sponsored by Wonder Bread and ... While challenging Bobby, Girard drives the #55 Perrier Chevrolet**Monte****Carlo**. Michael Clarke Duncan as Lucius Washington, ...###### Auguste Escoffier

In 1884, Escoffier and his wife moved to

**Monte****Carlo**, where Escoffier was employed by César Ritz, manager of the new Grand ... restaurateur and culinary writer who popularized and updated traditional French cooking**methods**. Much of Escoffier's technique ...###### Éric Moulines

... coupling estimation and simulation problems with

**Monte****Carlo**Markov Chain**Methods**(MCMC). He has also developed numerous ... Sequential**Monte****Carlo**smoothing for general state space hidden Markov models », The Annals of Applied Probability, 2011, pp. ... He is involved in the development of new waveform synthesis**methods**called PSOLA (pitch synchronous overlap and add). After ... He then devoted himself mainly to the application of Bayesian**methods**with applications in signal processing and statistics. ...###### Stratified sampling

In computational statistics, stratified sampling is a

**method**of variance reduction when**Monte****Carlo****methods**are used to ... This**method**is generally used when a population is not a homogeneous group. Proportionate allocation uses a sampling fraction ... In statistics, stratified sampling is a**method**of sampling from a population which can be partitioned into subpopulations. In ...###### Paul Wilson (nuclear engineer)

Engineering Toolkit Research contributed to new

**methods**in widely used radiation transport software such as the**Monte****Carlo**N- ... "Acceleration Techniques for Direct Use of CAD-Based Geometries in**Monte****Carlo**Radiation Transport." International Conference on ... the next generation fuel cycle simulator Lead developer of the Direct Accelerated Geometry**Monte****Carlo**Toolkit (DAGMC) CAD- ... "Adjoint-weighted tallies for k-eigenvalue calculations with continuous-energy**Monte****Carlo**." Nucl. Sci. Eng. 168, no. 3 (2011): ...###### Science and inventions of Leonardo da Vinci

Pedretti,

**Carlo**(2006). Leonardo da Vinci. Surrey: Taj Books International. ISBN 978-1-8440-6036-8.Pedretti,**Carlo**(1982). ... How and why I do not describe my**method**of remaining under water, or how long I can stay without eating; and I do not publish ... There is a legend that Leonardo tested the flying machine on**Monte**Ceceri with one of his apprentices, and that the apprentice ... I also have types of mortars that are very convenient and easy to transport.... when a place cannot be reduced by the**method**of ...###### Information-based complexity

In contrast the

**Monte****Carlo****method**gives only a stochastic assurance. See Sloan and Woźniakowski When are Quasi-**Monte****Carlo**... People in finance have long been using the**Monte****Carlo****method**(MC), an instance of a randomized algorithm. Then in 1994 a ... discovered that the quasi-**Monte****Carlo**(QMC)**method**using low discrepancy sequences beat MC by one to three orders of magnitude ... This research was published in the 1964 monograph Iterative**Methods**for the Solution of Equations. The general setting for ...###### GCMC

... a special operations group of the French Navy General Conference Mennonite Church Grand Canonical

**Monte****Carlo****methods**, a ...###### Review: H. A. Meyer, Symposium on **Monte** **Carlo** **methods**

**Monte** **Carlo** **Methods** - VideoLectures.NET

... importance sampling and standard Markov chain

**Monte****Carlo**(MCMC)**methods**. We will then discuss more advanced MCMC**methods**such ... importance sampling and standard Markov chain**Monte****Carlo**(MCMC)**methods**. We will then discuss more advanced MCMC**methods**such ... as adaptive MCMC**methods**and auxiliary variable**methods**such as parallel tempering, particle MCMC**methods**and slice sampling. ... as adaptive MCMC**methods**and auxiliary variable**methods**such as parallel tempering, particle MCMC**methods**and slice sampling. ...###### Introducing **Monte** **Carlo** **Methods** with R | R-bloggers - Part 3

Thats it!, "Introducing

**Monte****Carlo****Methods**with R" is out, truly out, I have received a copy from Springer by express mail ... Introducing**Monte****Carlo****Methods**with R. Typos in Chapter 3. January 7, 2010 , xian ... Here are two more typos in the exercises of Chapter 3 of "Introducing**Monte****Carlo****Methods**with R". - due to the (later) ... "Introducing**Monte****Carlo****Methods**with R" is out!. December 9, 2009 , xian ...###### Randomized quasi-**Monte** **Carlo** **methods** with applications to quantitative risk management

Erik Hintz (2022). Randomized quasi-

**Monte****Carlo****methods**with applications to quantitative risk management. UWSpace. http://hdl. ... We use randomized quasi-**Monte****Carlo**(RQMC) techniques to construct computational tools for working with normal mixture models, ... RQMC**methods**on triangles have recently been developed by K. Basu and A. Owen. We show that one of the proposed sequences has ... We explore how we can still use RQMC in this setting and propose several**methods**when sampling of W is only possible via a ...###### Calculate Pi with **Monte**-**Carlo**-**method** - JSXGraph Wiki

###### Advanced Markov Chain **Monte** **Carlo** **Methods**: Learning from Past Samples | Založba Pasadena

Advanced Markov Chain

**Monte****Carlo****Methods**: Learning from Past Samples. Markov Chain**Monte****Carlo**(MCMC)**methods**are now an ... Ocenite: Advanced Markov Chain**Monte****Carlo****Methods**: Learning from Past Samples. Če ste že vpisani med kupce v spletni knjigarni ... Priporočite: Advanced Markov Chain**Monte****Carlo****Methods**: Learning from Past Samples. E-naslov, kamor želite poslati izbrano ... A detailed discussion of the**Monte****Carlo**Metropolis-Hastings algorithm that can be used for sampling from distributions with ...###### An introduction to **Monte** **Carlo** **method** for the Boltzmann equation | ESAIM: Proceedings and Surveys

An introduction to

**Monte****Carlo****method**for the Boltzmann equation. Lorenzo Pareschi and Giovanni Russo ... Probabilistic tools and**Monte**-**Carlo**approximations for some Boltzmann equations ESAIM: Proc., 2001, Vol. 10, p. 77-126. ... Numerical**methods**for Vlasov-Lorentz models ESAIM: Proc., 2001, Vol. 10, p. 201-210. ... A redistribution**method**for axisymmetric diffusion ESAIM: Proc., 1999, Vol. 7, p. 387-396. ...###### Multilevel and Quasi **Monte** **Carlo** **Methods** for the Calculation of the Expected Value of Partial Perfect Information<...

In this paper, we explore the potential of Quasi

**Monte**-**Carlo**(QMC) and Multilevel**Monte**-**Carlo**(MLMC) estimation to reduce ... In this paper, we explore the potential of Quasi**Monte**-**Carlo**(QMC) and Multilevel**Monte**-**Carlo**(MLMC) estimation to reduce ... In this paper, we explore the potential of Quasi**Monte**-**Carlo**(QMC) and Multilevel**Monte**-**Carlo**(MLMC) estimation to reduce ... In this paper, we explore the potential of Quasi**Monte**-**Carlo**(QMC) and Multilevel**Monte**-**Carlo**(MLMC) estimation to reduce ...###### An introduction of simulation utilizing the **Monte** **Carlo** **method** of analysis as a tool for U.S. Coast Guard personnel...

###### Improved **Monte**-**Carlo** **method** vs. hit-and-miss **method** | Statistics Help @ Talk Stats Forum

... the hit-and-miss

**method**or the improved**Monte**-**Carlo****method**?*... ... Improved**Monte**-**Carlo****method**vs. hit-and-miss**method**. * Thread ... variance of hit-and-miss**method**),0. \(\sigma^2_M-\sigma^2_H,0\). Doesnt it imply improved**Monte**-**Carlo****method**has a higher ... I am not understanding *Which is more accurate, the hit-and-miss**method**or the improved**Monte**-**Carlo****method**?*. http://www-stat. ...###### Estimate Pi by **Monte** **Carlo** **method** - MATLAB Cody - MATLAB Central

**Carlo**_

**method**\,,w:r,,w:t,https://en.wikipedia.org/wiki/

**Monte**_

**Carlo**_

**method**,/w:t,,/w:r,,/w:hyperlink,,/w:p,,/w:body,,/w:document ... We can estimate the value of pi with random number by

**Monte**

**Carlo**

**method**. ,/w:t,,/w:r,,/w:p,,w:p,,w:pPr,,w:pStyle w:val=\text ... We can estimate the value of pi with random number by

**Monte**

**Carlo**

**method**. ,/span,,/span,,/div,,div style=block-size: 21px; ... w:t,,/w:r,,w:hyperlink w:docLocation=\https://en.wikipedia.org/wiki/

**Monte**_ ...

###### Assessment of a fully 3D **Monte** **Carlo** reconstruction **method** for preclinical PET with iodine-124 - Inserm - Institut national de...

The aim of this work was to assess the quantitative performance of a fully 3D

**Monte****Carlo**(MC) reconstruction for preclinical I ... Assessment of a fully 3D**Monte****Carlo**reconstruction**method**for preclinical PET with iodine-124 M. Moreau 1, 2 I. Buvat 1, 2 L ... Assessment of a fully 3D**Monte****Carlo**reconstruction**method**for preclinical PET with iodine-124. Physics in Medicine and Biology ... The aim of this work was to assess the quantitative performance of a fully 3D**Monte****Carlo**(MC) reconstruction for preclinical I ...###### Water | Free Full-Text | Simple and Low-Cost Procedure for Monthly and Yearly Streamflow Forecasts during the Current...

... the two-parameter Gamma continuous cumulative probability distribution function and the

**Monte****Carlo****method**. Several model ...**Monte****Carlo****Method**The**Monte****Carlo****Method**is a numerical statistical**method**that allows the replication of random behaviour of ... Rubinstein, R.Y.; Kroese, D.P. Simulation and the**Monte****Carlo****Method**; John Wiley & Sons: Hoboken, NJ, USA, 2016. [Google ... Assigning Probabilities and Application of**Monte****Carlo****Method**As explained in Section 2.6, we obtained 10,000 random observed ...###### Probabilistic regressor chains with **Monte** **Carlo** **methods**

... Read J.;Martino L. 2020. Abstract. A large number and diversity of ...

**Monte****Carlo****methods**. Multi-label classification. Multi-output regression. Particle filters. Regressor chains ... In particular we present**Monte****Carlo**schemes in the framework of probabilistic chains. We show they can be effective, flexible ... In particular we present**Monte****Carlo**schemes in the framework of probabilistic chains. We show they can be effective, flexible ...###### Application of the **Monte** **Carlo** **Method** for the Estimation of Uncertainty in Radiofrequency Field Spot Measurements

... ... 8] Azpurua, M., Tremola, C., Paez, E. (2011). Comparison of the GUM and

**Monte****Carlo****methods**for the uncertainty estimation in ... Propagation of distributions using a**Monte****Carlo****method**, 1st Edition. JCGM 101:2008.. Search in Google Scholar ... Implementation in MATLAB of the adaptive**Monte****Carlo****method**for the evaluation of measurement uncertainties. Accreditation and ...###### A Markov Chain **Monte** **Carlo** **Method** for Derivative Pricing and Risk Assessment

... Sanjiv R. Das and Alistair Sinclair ...

**Monte****Carlo**simulation is used to estimate the lattice value by sampling appropriately from the nodes. Most sampling**methods**... This paper presents a Markov chain**Monte****Carlo**scheme, adapted from Sinclair and Jerrum (Information and Computation 82 (1989 ... This partial information is used to direct the sampling, in similar fashion to traditional importance sampling**methods**. The key ...###### Repositório Institucional da UnB: **Monte** **Carlo** **methods** on low and high energy atmospheric phenomena

**Monte**

**Carlo**

**methods**on low and high energy atmospheric phenomena. 2020. xviii, 143 f., il. Tese (Doutorado em Física)- ...

**Monte**

**Carlo**

**methods**on low and high energy atmospheric phenomena. pt_BR. ... Através de simulações

**Monte**

**Carlo**, analiza-se os campos elétricos necessários para colocar um elétrons em estado de runaway. ...

**Monte**

**Carlo**simulations are implemented to investigate the probability of low electric fields driving electrons to runaway ...

###### Heuristic **Monte** **Carlo** **method** applied to cooperative motion algorithm for binary lattice fluid - IOS Press

While the first

**method**is the well-established Metr ... The Cooperative Motion Algorithm is an efficient lattice**method**... Heuristic**Monte****Carlo****method**applied to cooperative motion algorithm for binary lattice fluid Article type: Research Article ... While the first**method**is the well-established Metropolis algorithm, the other one is an heuristic algorithm which needs ... We compare both**methods**, calculating the energy as well as heat capacity as a function of temperature. The critical temperature ...###### 2105.00414] Predicting highly correlated hydride-ion diffusion in SrTiO$ 3$ crystals
based on the fragment kinetic **Monte**...

... crystals based on the fragment kinetic

**Monte****Carlo****method**with machine-learning potential. Authors: Hiroya Nakata ... In this study, we investigate the hydride-ion migration mechanism using a kinetic**Monte****Carlo**approach to understanding the ... The difficulties in applying the**method**to hydride and oxygen ion migration involve complex changes in the ionic migration ... The parallel-processing efficiency of our proposed**method**was 84.92 \% for our 1,000-CPU implementation, suggesting that the ...###### Simulation of Electron Transport in InGaAs/AlGaAs HEMTs Using an Electrothermal **Monte** **Carlo** **Method**<...

Simulation of Electron Transport in InGaAs/AlGaAs HEMTs Using an Electrothermal

**Monte****Carlo****Method**. / Sadi, T.; Kelsall, R.; ... title = "Simulation of Electron Transport in InGaAs/AlGaAs HEMTs Using an Electrothermal**Monte****Carlo****Method**", ... Simulation of Electron Transport in InGaAs/AlGaAs HEMTs Using an Electrothermal**Monte****Carlo****Method**. ... T1 - Simulation of Electron Transport in InGaAs/AlGaAs HEMTs Using an Electrothermal**Monte****Carlo****Method**...**Monte** **Carlo** **Method** Archives - OLECD

###### Archiwa: **Monte** **Carlo** **method** - Agile Institute

###### Browsing by Subject "**Monte**-**Carlo** **method**"

###### mVMC | many-variable variational **Monte** **Carlo** **method**

SimulationsMarkov Chain Monte CQuasi-Monte Carlo mEconometricsAlgorithmIntroducing Monte Carlo MAdvanced MCMC methodsEstimateMCMCStochastic approximationDeterministicMultilevelBayesianUncertaintyStatisticalProbabilisticNumerical methodsOptimizationRegressionCalculationNumericallyAdaptiveParallelSmall Area EstimAlgorithmsTransport SimulationAnalysesSamplesComputational MethodsProhibitivelyQuantitativeEfficiencyMethodologyClassificationLatticePhysicsEstimation methodDynamics2021MethodologicalVarianceRadiationStudyApplicabilitySimulation-basedPredictionParameterAnalysisMathematicsDataIntroductionApproachesFrameworkRandomWorkshopCalculateParis

###### Simulations7

- This book discusses recent developments of MCMC methods with an emphasis on those making use of past sample information during simulations. (pasadena.si)
- The parallel-processing efficiency of our proposed method was 84.92 \% for our 1,000-CPU implementation, suggesting that the approach should be widely applicable to simulations of ionic migration in crystals at a reasonable computational cost. (cornell.edu)
- Monte Carlo simulations are implemented to investigate the probability of low electric fields driving electrons to runaway state. (unb.br)
- Markov chain Monte Carlo simulations allow researchers to approximate posterior distributions that cannot be directly calculated. (cdc.gov)
- The Monte Carlo simulations provided in this article show that our estimators perform well. (accessecon.com)
- To validate the applicability of TIGRE to pCT, several Monte Carlo simulations modeling a pCT setup with two Catphan® modules as phantoms were performed. (physicamedica.com)
- Using a combination of analytic methods and Monte Carlo simulations, we study the morphology of growing steps in detail. (aalto.fi)

###### Markov Chain Monte C1

- The estimation procedure is implemented based on Markov chain Monte Carlo methods. (revolutionanalytics.com)

###### Quasi-Monte Carlo m1

- Eighth International Conference on Monte Carlo and Quasi-Monte Carlo Methods in Scientific Computing, Montreal, July 2008. (imag.fr)

###### Econometrics1

- These include, for example, methods of econometrics or Monte-Carlo techniques and computer-intensive procedures on the one hand and special courses in survey statistics on the other. (uni-trier.de)

###### Algorithm7

- A detailed discussion of the Monte Carlo Metropolis-Hastings algorithm that can be used for sampling from distributions with intractable normalizing constants. (pasadena.si)
- The Cooperative Motion Algorithm is an efficient lattice method to simulate dense polymer systems and is often used with two different criteria to generate a Markov chain in the configuration space. (iospress.com)
- While the first method is the well-established Metropolis algorithm, the other one is an heuristic a lgorithm which needs justification. (iospress.com)
- The same algorithm implemented using pepper.js can be found on the Monte Carlo Estimate for Pi site. (curiosity-driven.org)
- Most of this lesson's content is devoted to studying the ray-marching algorithm but you should know that while this algorithm was used almost exclusively for volume rendering until relatively recently (the mid-2010s at least), modern rendering engines are now generally using a stochastic Monte-Carlo based approach with it comes to rendering volumes instead. (scratchapixel.com)
- For historical reasons and because it's much easier to get introduced to the topic of volume rendering (and the Volume Rendering Equation) through the ray-marching algorithm than through stochastic methods that are significantly more complex (particularly from the point of view of someone new to CGI programming with little to no math background). (scratchapixel.com)
- At the end of the module, you will be able to formalise a ML task, choose the appropriate method to process it numerically, implement the ML algorithm in Python, and assess the method¿s performance. (qmul.ac.uk)

###### Introducing Monte Carlo M4

- Here are two more typos in the exercises of Chapter 3 of "Introducing Monte Carlo Methods with R". - due to the (later) inclusion of an extra-exercise in the book, the "above exercise" in Exercise 3.5 actually means Exercise 3.3. (r-bloggers.com)
- When grading homeworks for my Monte Carlo graduate class, I found that my students had pointed out two typos in the exercises of Chapter 2 of "Introducing Monte Carlo Methods with R". - In Exercise 2.17, question d. should be "d. (r-bloggers.com)
- Introducing Monte Carlo Methods with R" is out, truly out, I have received a copy from Springer by express mail today! (r-bloggers.com)
- Following a proposal by Springer-Verlag Paris, I have decided to translate Introducing Monte Carlo Methods with R with George Casella into French, since a new collection of R books (in French) is planed for the Spring of 2010. (r-bloggers.com)

###### Advanced MCMC methods1

- We will then discuss more advanced MCMC methods such as adaptive MCMC methods and auxiliary variable methods such as parallel tempering, particle MCMC methods and slice sampling. (videolectures.net)

###### Estimate9

- In this paper, we develop methods to apply QMC and MLMC to EVPPI, addressing particular challenges that arise where Markov Chain Monte Carlo (MCMC) has been used to estimate input parameter distributions. (bris.ac.uk)
- We can estimate the value of pi with random number by Monte Carlo method. (mathworks.com)
- Instead, Monte Carlo simulation is used to estimate the lattice value by sampling appropriately from the nodes. (joim.com)
- In RL Monte Carlo methods allow us to estimate values directly from experience, from sequences of states, actions and rewards. (coursera.org)
- By the end of this video you will be able to understand how Monte Carlo methods can be used to estimate value functions from sampled interaction and identify problems that can be solved using Monte Carlo methods. (coursera.org)
- Monte Carlo (named for the casino in Monaco) methods estimate a distribution by random sampling. (cdc.gov)
- Abstract use this method to estimate the size of local populations eligible for, or in need of, preventive health services and Introduction interventions. (cdc.gov)
- This study aims to estimate the lower limits for feasible Ra-223 single-photon emission computerized tomography (SPECT) imaging using a Monte Carlo simulation study .Methods:The SPECT images were produced on a homemade code: the Monte Carlo simulation of electrons and photons for SPECT (MCEP-SPECT). (kyushu-u.ac.jp)
- This paper revisits the Two-Sample Two-Stage Least Squares (TSTSLS) method, which is commonly used to estimate intergenerational mobility in the absence of parental earnings data. (ssrn.com)

###### MCMC5

- We will first review the Monte Carlo principle and standard Monte Carlo methods including rejection sampling, importance sampling and standard Markov chain Monte Carlo (MCMC) methods. (videolectures.net)
- Markov Chain Monte Carlo (MCMC) methods are now an indispensable tool in scientific computing. (pasadena.si)
- We illustrate the methods using a two examples: a simplified decision tree model for treatments for depression, and a complex Markov model for treatments to prevent stroke in atrial fibrillation, both of which use MCMC inputs. (bris.ac.uk)
- A Markov chain Monte Carlo (MCMC) simulation is a method of estimating an unknown probability distribution for the outcome of a complex process (a posterior distribution). (cdc.gov)
- We will discuss the MCMC method. (tifr.res.in)

###### Stochastic approximation2

- Key Features: Expanded coverage of the stochastic approximation Monte Carlo and dynamic weighting algorithms that are essentially immune to local trap problems. (pasadena.si)
- Mini-symposium on Stochastic Approximation at the International Conference on Monte Carlo techniques , 2016, France, Paris. (imag.fr)

###### Deterministic3

- As described in detail in [ 2 ], the B 1 MC method generates the homogenized few-group constants of fuel assemblies or fuel bundles in much the same way as its deterministic counterparts [ 3 - 5 ]. (hindawi.com)
- Because of these characteristics of treating the nuclear cross section and geometrical data input exactly, the B 1 MC method may perform inherently more exact IMS calculations, which in turn makes subsequent CS calculations conducted on more precise multi-group B 1 equations, than its deterministic counterparts. (hindawi.com)
- Deterministic and Stochastic (Monte-Carlo) based design methods for radiation shielding and protection. (tum.de)

###### Multilevel5

- In this paper, we explore the potential of Quasi Monte-Carlo (QMC) and Multilevel Monte-Carlo (MLMC) estimation to reduce computational cost of estimating EVPPI by reducing the variance compared with MC, while preserving accuracy. (bris.ac.uk)
- Multilevel approaches, such as multilevel Monte Carlo (MLMC), can reduce the complexity significantly when they are combined with a fast multigrid solver, but to exploit them fully in a parallel environment, sophisticated scheduling strategies are needed. (drzisga.dev)
- Mini-symposium on Multilevel Monte Carlo Methods at the SMAI Congrès 2015, France, Savoie. (imag.fr)
- Recently, considerable research has been done on multilevel, model-based, small-area estimation methods ( 10 , 13 - 15 ). (cdc.gov)
- These methods can produce data on variations in the multilevel influence of local social and physical environments on health outcomes among people in small areas by using various demographic characteristics (eg, age, sex, race/ethnicity). (cdc.gov)

###### Bayesian1

- In Bayesian inference, the model space is directly probed by sampling methods such that we obtain a reliable uncertainty appraisal, determine optimal models, and avoid entrapment in a small local region of the model space. (nsf.gov)

###### Uncertainty6

- 2008). Evaluation of measurement data - Supplement 1 to the 'Guide to the expression of uncertainty in measurement' - Propagation of distributions using a Monte Carlo method, 1st Edition. (sciendo.com)
- Comparison of the GUM and Monte Carlo methods for the uncertainty estimation in electromagnetic compatibility testing. (sciendo.com)
- This discussion paper describes the methods used to quantify uncertainty in the various inputs to LE and HALE estimates, and how these uncertainties were incorporated in intervals around the reported measures. (who.int)
- Modern epidemiological techniques report confidence or uncertainty intervals around all estimates, and there is a growing literature on methods for capturing uncertainty in quantitative policy analyses (see, for example, Morgan and Henrion (7) , King et al. (who.int)
- For some simple quantities of interest, such as linear combinations of normally distributed random variables, uncertainty may be reasonably captured using analytic methods. (who.int)
- We describe the methods used to combine the uncertainty from each input into the computations of HALE, and end with a discussion of continuing work and future directions in this area. (who.int)

###### Statistical7

- The method is often used to solve problems that are hard to determine exactly, when there is enough statistical data available. (buddygo.net)
- The solution of such a statistical inverse method is completely described by the posterior distribution, which quantifies the distributions for parameters and inversion uncertainties. (nsf.gov)
- This module begins by covering some of the essential theoretical notions of probability and the distributions of random variables which underpin statistical methods. (qmul.ac.uk)
- C. H. Kapadi and R. L. Thomasson, "On Estimating the Parameter of the Truncated Geometric Distribution by the Method of Moments," Annals of the Institute of Statistical Mathematics, Vol. 20, 1975, pp. 519-532. (scirp.org)
- JD Felske,, Reviewer 15 01 2003 radiative transfer statistical analysis Monte Carlo methods ray tracing reviews 1R48. (asme.org)
- Besides, the analysis and statistical modelling, the Logistic Regression method was used. (preprints.org)
- The use of statistical and mathematical methods to analyze biological observations and phenomena. (bvsalud.org)

###### Probabilistic3

- In particular we present Monte Carlo schemes in the framework of probabilistic chains. (unict.it)
- Variability in human response can be treated effec- tively using probabilistic methods. (cdc.gov)
- METHODS: We estimated the incremental number of pneumococcal disease events and deaths averted, costs per quality adjusted life-year (QALY) gained, and costs per life-year gained under different vaccination strategies using a probabilistic model following a single birth cohort of 3.9 million individuals (based on 2020 U.S. birth cohort). (cdc.gov)

###### Numerical methods4

- The procedure offers a great advantage over the analytic solution of the problem and usual shell numerical methods when one wants to determine the dome geometry with constant stresses, since the presented procedure has the goal stress as input value for obtaining the geometry, as opposed to the usual numerical methods, where the reverse occurs. (scite.ai)
- Third Conference on Numerical Methods in Finance, Paris, April 2009. (imag.fr)
- Conference on Numerical Methods in Finance, Udine (Italy), June 2008. (imag.fr)
- The modelling of structures and processes at these vastly different scales requires rather different theoretical and numerical methods, from quantum chemistry methods on the atomic scale to continuum models on the macroscopic scale. (psi-k.net)

###### Optimization3

- Additionally, local optimization-based FWI methods cannot always converge to a geologically meaningful solution unless the inversion starts with an accurate background model. (nsf.gov)
- We demonstrate the potential of this new computational framework by performing a linear coseismic slip inversion through adjoint-based optimization methods, without requiring computation of elastic Green's functions. (nsf.gov)
- This feature makes unsuitable of traditional methods for optimization of the adequacy of electric power system. (e3s-conferences.org)

###### Regression4

- The procedure innovatively combines the use of well-known regression analysis techniques, the two-parameter Gamma continuous cumulative probability distribution function and the Monte Carlo method. (mdpi.com)
- Chaining methods have often providing state of the art results, and the idea of extending it to multi-output regression has already been trialed. (unict.it)
- This module will introduce you to some of the most widely-used techniques in machine learning (ML). After reviewing the necessary background mathematics, we will investigate various ML methods, such as linear regression, polynomial regression and classification with logistic regression. (qmul.ac.uk)
- Assessing meta-regression methods for examining moderator relationships with dependent effect sizes: A Monte Carlo simulation. (bvsalud.org)

###### Calculation3

- L. Teich, C. Schröder, C. Müller, A. V. Patel, J. Meyer, and A. Hütten, “Efficient Calculation of Low Energy Configurations of Nanoparticle Ensembles for Magnetoresistive Sensor Devices by means of Stochastic Spin Dynamics and Monte Carlo Methods,” presented at the The European Conference Physics on Magnetism, Poznan, 2014. (fh-bielefeld.de)
- Teich L, Schröder C, Müller C, Patel AV, Meyer J, Hütten A. Efficient Calculation of Low Energy Configurations of Nanoparticle Ensembles for Magnetoresistive Sensor Devices by means of Stochastic Spin Dynamics and Monte Carlo Methods. (fh-bielefeld.de)
- In the calculation, the general method with the linear creep theory was applied. (scite.ai)

###### Numerically2

- We then translate these results into large-time asymptotics for call options and implied volatility and we verify our results numerically using Monte Carlo simulation. (zbmath.org)
- This article examines numerically the flexibility influence of support beams in static response and dynamic properties of a symmetric plate formed by massive slabs of reinforced concrete in elastic linear regime, using the Finite Element Method. (scite.ai)

###### Adaptive1

- Implementation in MATLAB of the adaptive Monte Carlo method for the evaluation of measurement uncertainties. (sciendo.com)

###### Parallel1

- From a computational perspective, my research interests have focused on Markov chain Monte Carlo and parallel computing methods in computational statistics. (osu.edu)

###### Small Area Estim1

- Another advantage is that model-based small-area estimation methods borrow information from both individual-level data within the survey sample and from area-level covariates external to the original sample, and they tend to generate smoothed estimates with better precision ( 16 ). (cdc.gov)

###### Algorithms1

- We use randomized quasi-Monte Carlo (RQMC) techniques to construct computational tools for working with normal mixture models, which include automatic integration routines for density and distribution function evaluation, as well as fitting algorithms. (uwaterloo.ca)

###### Transport Simulation1

- The method presented in this paper uses a detailed Monte Carlo radiation transport simulation in one step from source to dose rate. (ans.org)

###### Analyses1

- The applicability of the B 1 MC method to PWR core analyses has been demonstrated by showing that few-group constants from the method implemented in a Seoul National University (SNU) MC code, McCARD [ 6 ] lead to nodal core neutronics calculations in a good agreement with whole PWR core reference MC calculations [ 2 ]. (hindawi.com)

###### Samples3

- We optimize the concurrent execution across the three layers of the MLMC method: parallelization across levels, across samples, and across the spatial grid. (drzisga.dev)
- With this study, we aimed to validate an intra-laboratory molecular detection method for SARS-CoV-2 on saliva samples collected in a new storage saline solution, comparing the results to NP swabs to determine the difference in sensitivity between the two tests. (bvsalud.org)
- Internal method validation was performed to standardize the entire workflow for saliva samples. (bvsalud.org)

###### Computational Methods1

- The conference aims at bringing together researchers and practitioners to discuss recent developments in computational methods, methodology for data analysis and applications in statistics. (compstat2016.org)

###### Prohibitively1

- Use of the surveillance methods for obtaining national (ie, large-area) data to obtain small-area data on childhood obesity is prohibitively expensive. (cdc.gov)

###### Quantitative1

- The aim of this work was to assess the quantitative performance of a fully 3D Monte Carlo (MC) reconstruction for preclinical I-124 PET. (inserm.fr)

###### Efficiency2

- They preserve and maintain stationary data structure of the process and are reliable for predictive purposes, confirming the efficiency of the proposed method. (scirp.org)
- Furthermore, brushing has the same efficiency as a chemical method for biofilm removal 14 . (bvsalud.org)

###### Methodology1

- Second, we use administrative data from a developing country to test our lower bound methodology through an Empirical Monte Carlo approach, confirming its validity. (ssrn.com)

###### Classification1

- Cartographic classification methods present a simplified way to examine some classification and clustering methods, and these will be explored in more depth with example applications. (ucgis.org)

###### Lattice2

- This paper presents a Markov chain Monte Carlo scheme, adapted from Sinclair and Jerrum (Information and Computation 82 (1989)), that is able to overcome this problem, provided some partial (possibly very inaccurate) information about the lattice sum is available. (joim.com)
- The critical temperature, which was determined using the Binder cumulant, was the same for all methods with the simulation accuracy and in agreement with the exact critical temperature for the Ising model on the 2D triangular lattice. (iospress.com)

###### Physics4

- Whenever possible, we draw connections between image-synthesis techniques and methods from particle physics and neutron transport to provide the reader with a broader context. (disneyresearch.com)
- We review the main software and computing challenges for the Monte Carlo physics event generators used by the LHC experiments, in view of the High-Luminosity LHC (HL-LHC) physics programme. (springer.com)
- For ongoing commitment to developing physics in Africa through initiating the African School on Electronic Structure Methods and Applications and leadership in bringing together African physicists from across the continent to create a Pan-African physics communication vehicle. (aps.org)
- During his career, he organized or co-organized multiple international conferences and workshops promoting computational physics in general and the applications and development of quantum Monte Carlo methods. (aps.org)

###### Estimation method3

- The term Monte Carlo is often used more broadly for any estimation method that relies on repeated random sampling. (coursera.org)
- Knutson K, Zhang W, Hispanic women varied more than did those of women of Tabnak F. Applying the smal -area estimation method to other races. (cdc.gov)
- We used the smal -area estimation method to determine implemented locally, in counties or cities (2). (cdc.gov)

###### Dynamics1

- J Zehnder,, Reviewer atmospheric movements meteorology modelling Navier-Stokes equations flow simulation finite difference methods geophysical fluid dynamics radiative transfer 9R53. (asme.org)

###### 20211

- METHODS: The Centers for Disease Control and Prevention collected data from health departments on workplace COVID-19 outbreaks from August through October 2021: the number of workplace outbreaks, by workplace setting, and the total number of cases among workers linked to these outbreaks. (cdc.gov)

###### Methodological3

- In these modules, advanced methods of statistics in general and inferential statistics in particular are taught, as well as further methodological and content-related emphases. (uni-trier.de)
- Method: Qualitative research using symbolic interactionism as a theoretical reference and narrative research as a methodological reference. (bvsalud.org)
- Method: Study of qualitative approach, whose theoretical and methodological frameworks. (bvsalud.org)

###### Variance2

- Doesn't it imply improved Monte-Carlo method has a higher variance? (talkstats.com)
- This paper describes detailed far-field dose rate calculations performed for a proposed CISF using MAVRIC, the Monte Carlo radiation shielding sequence in SCALE 6.2.3, with automated variance reduction based on discrete ordinates calculations. (ans.org)

###### Radiation1

- Basic Methods for Radiation Dose Calculations. (tum.de)

###### Study11

- In this study, we investigate the hydride-ion migration mechanism using a kinetic Monte Carlo approach to understanding the relationship between the hydride and oxygen ions. (cornell.edu)
- In this work, we propose an improved 3D Monte Carlo Potts (MCP) method to quantitatively study the relationship between non-uniform temperature fields and final grain morphologies. (techscience.com)
- This knowledge area embodies a variety of data driven analytics, geocomputational methods, simulation and model driven approaches designed to study complex spatial-temporal problems, develop insights into characteristics of geospatial data sets, create and test geospatial process models, and construct knowledge of the behavior of geographically-explicit and dynamic processes and their patterns. (ucgis.org)
- We introduce for the first time the grand-canonical Monte Carlo method to study the growth/dissolution steps of nanoparticle growth mediated by seeds. (nau.edu)
- The main purpose of this study is to present a new method for determining the situations in which, dispersion coefficient has significant effect on solute transport mechanism. (ac.ir)
- 1996). However, these studies did value, this study provides an example of this method not attempt to derive guidance values. (cdc.gov)
- Akihiko Takahashi, Hibiki Ueno, Shingo Baba, Masayuki Sasaki, Estimation of the lower limits for feasible Ra-223 SPECT imaging: a Monte Carlo simulation study, Asia Oceania Journal of Nuclear Medicine & Biology , 2021.06, Objective(s):Ra-223 is a promising radionuclide for the treatment of skeletal metastases in castration-resistant prostate cancer patients. (kyushu-u.ac.jp)
- Method: This is a descriptive study with a qualitative approach, based on Merleau-Ponty's phenomenology and performed at the Fernando Magalhães Maternity Hospital in the state of Rio de Janeiro, through interviews wi. (bvsalud.org)
- Method: a cross-sectional study based on records data of preterm newborns hospitalized in two neonatal units in northwest Paraná State in 2015. (bvsalud.org)
- Method: Exploratory, qualitative study conducted at a Neonatal Intensive Care Unit from a University Hospital in the state capital of southern B. (bvsalud.org)
- Method: a qualitative study with 11 nurses from Neonatal Intensive Care Units of a city in the State of São Paulo countryside, based on the Developmental Care. (bvsalud.org)

###### Applicability1

- To examine the applicability of the B 1 MC method for the CANDU 6 core analysis, the fuel bundle cell and supercell calculations are performed using it to obtain the two-group constants. (hindawi.com)

###### Simulation-based1

- Methods A gamma camera simulation based on the Monte Carlo method was performed to produce SPECT images. (kyushu-u.ac.jp)

###### Prediction1

- You will learn about on-policy and off-policy methods for prediction and control, using Monte Carlo methods---methods that use sampled returns. (coursera.org)

###### Parameter1

- We consider Monte Carlo sampling methods for parameter estimation and inference under nonlinear and non-Gaussian assumptions. (cdc.gov)

###### Analysis6

- An introduction of simulation utilizing the Monte Carlo method of analysis as a tool for U.S. Coast Guard personnel administration. (nps.edu)
- As an alternative way to generate the two-group constants necessary for the CANDU-PHWR core analysis, this paper proposes utilizing a B 1 theory augmented Monte Carlo (MC) few-group constant generation method (B 1 MC method) which has been devised for the PWR fuel assembly analysis method. (hindawi.com)
- The purpose of this paper is to demonstrate that the B 1 MC method is also applicable to the neutronics analysis of CANDU-PHWRs by showing that homogenized two-group constants of fuel bundles of CANDU 6 from it can result in core neutronics calculations that agree very well with a reference CANDU 6 whole core analysis. (hindawi.com)
- For analysis purposes, the Monte Carlo method was adopted, followed by the First Order Reliability Method (FORM). (scite.ai)
- The reliability analysis of the variants of development of electric power system is carried out on the base of the Monte Carlo method. (e3s-conferences.org)
- Monte Carlo analysis of impact of underascertainment of mesothelioma cases on underestimation of risk. (cdc.gov)

###### Mathematics1

- T. Olatayo, "On the Application of Bootstrap Method to Stationary Time Series Process," American Journal of Computational Mathematics , Vol. 3 No. 1, 2013, pp. 61-65. (scirp.org)

###### Data5

- However, discrepancies exist among these models due to differences in both data sets and tomographic methods, which introduce uncertainties on the imaged lithospheic structure beneath North America. (nsf.gov)
- A further model refinement using the best data coverage and advanced tomographic methods such as full-waveform inversion (FWI) is expected to provide better seismological constraints. (nsf.gov)
- The performance of the different methods is studied on computer-simulated and controlled laboratory-generated data. (cdc.gov)
- There are, however, cost-effective methods of generating health-related data, particularly on obesity, for small-area populations ( 10 - 12 ). (cdc.gov)
- A structured self-report data collection method was applied to elicit data about the partici- pants' knowledge and circumstances that prevent them from reporting child abuse. (who.int)

###### Introduction2

###### Approaches1

- Thankfully with the continuous rise in computing power, we can now produce results with the stochastic method within reasonable times, and since it creates better results, the ray-marching method has been phased out in favor of stochastic-based approaches instead. (scratchapixel.com)

###### Framework1

- SUMMARY We introduce a new finite-element (FE) based computational framework to solve forward and inverse elastic deformation problems for earthquake faulting via the adjoint method. (nsf.gov)

###### Random2

- We explore how we can still use RQMC in this setting and propose several methods when sampling of W is only possible via a black box random variate generator. (uwaterloo.ca)
- Recall the Box-Muller method which transforms pairs of uniformly-distributed random variables to obtain a pair of independent standard normal random variates. (warwick.ac.uk)

###### Workshop1

- Invited to the Workshop on Monte Carlo Methods, Ecole Polytechnique, October 2012. (imag.fr)

###### Calculate1

- The one notable difference is that, unlike the model used to calculate national level estimates, the software does not use Monte-Carlo methodologies to provide ranges of estimates. (cdc.gov)

###### Paris1

- International Conference on Monte Carlo techniques , Paris, July 2016. (imag.fr)