###### Sieve empirical likelihood ratio tests for nonparametric functions - Kent Academic Repository
Fan, Jianqing and Zhang, Jian (2004) Sieve empirical likelihood ratio tests for nonparametric functions. Annals of Statistics, ... The likelihood ratio statistics are constructed based on the assumption that the distributions of stochastic errors are in a ... Generalized likelihood ratio statistics have been proposed in Fan, Zhang and Zhang [Ann. Statist. 29 (2001) 153-193] as a ... The proposed approach has two advantages over the generalized likelihood ratio method: it requires one only to specify some ...
https://kar.kent.ac.uk/597/
###### Image Analysis, Random Fields and Dynamic Monte Carlo Methods: A Mathematical Introduction by Gerhard Winkler, Paperback |...
Maximum Likelihood Estimators.- 13.1 Introduction.- 13.2 The Likelihood Function.- 13.3 Objective Functions.- 13.4 Asymptotic ... 14.4 The Maximum Likelihood Method.- 14.5 Computation of ML Estimators.- 14.6 Partially Observed Data.- VI. Supplement.- 15. A ... Concave Functions.- D. A Global Convergence Theorem for Descent Algorithms.- References. ...
https://www.barnesandnoble.com/w/image-analysis-random-fields-and-dynamic-monte-carlo-methods-gerhard-winkler/1112060636?ean=9783642975240
###### Composite likelihood approach to finite normal mixture models - Statistics and Actuarial Science - Simon Fraser University
A composite likelihood EM algorithm is used to maximize the penalized pairwise log-likelihood function. We prove that the CL-EM ... A composite likelihood consists of a combination of valid likelihood objects. It is shown to be an good and practical ... The composite likelihood approach has demonstrated its advantage in a number of applications. For a few but important cases the ... In this talk, we propose to use composite likelihood method for analyzing multivariate normal mixture models. Some statistical ...
http://www.stat.sfu.ca/research/seminars/abstracts/ZJin.html
###### CRAN Task View: Bayesian Inference
function in Hmisc derives the posterior (and optionally) the predictive distribution when both the prior and the likelihood are ... BayesSummaryStatLM provides two functions: one function that computes summary statistics of data and one function that carries ... dclone provides low level functions for implementing maximum likelihood estimating procedures for complex models using data ... bridgesampling provides R functions for estimating marginal likelihoods, Bayes factors, posterior model probabilities, and ...
http://vps.fmvz.usp.br/CRAN/web/views/Bayesian.html
###### "Markov Chain Monte Carlo With Application to Image Denoising" by Jakub Michel
This algorithm can be used in such a way that it takes into account the prior distribution and likelihood function, carrying a ... This algorithm can be used in such a way that it takes into account the prior distribution and likelihood function, carrying a ...
https://bearworks.missouristate.edu/theses/1649/
###### Likelihoodfunction - Wikipedia
When considered a function of N for fixed n, this is a likelihood function. The maximum likelihood estimate for N is n (by ... In statistics, a likelihood function (often simply the likelihood) is a function of the parameters of a statistical model given ... In such a situation, the likelihood function factors into a product of individual likelihood functions. The logarithm of this ... The relative likelihood is closely related to the likelihood ratio used in the likelihood-ratio test. The likelihood ratio is ...
https://en.wikipedia.org/wiki/Likelihood_function
###### likelihoodfunction
... I have been asked to write down the likelihood function for θ based upon the four given independant tests ... Write down the likelihood function for θ based upon these four given independant tests. What value of θ maximises this function ... Write down the likelihood function for θ based upon these four given independant tests. What value of θ maximises this function ... I have been asked to write down the likelihood function for θ based upon the four given independant tests and then find the ...
###### Partial LikelihoodFunction for the Cox Model
The exact likelihood is The Breslow likelihood is The Efron likelihood is Discrete Time Scale. Let Qi denote the set of all ... The discrete logistic likelihood is When there are no ties on the event times (that is, ), all four likelihood functions , , , ... In a stratified analysis, the partial likelihood is the product of the partial likelihood functions for the individual strata. ... Partial Likelihood Function for the Cox Model Let zl denote the vector of (possibly time-dependent) explanatory variables for ...
http://v8doc.sas.com/sashtml/stat/chap49/sect16.htm
###### LikelihoodFunction - Exponential Distribution | Physics Forums - The Fusion of Science and Community
Similar Discussions: Likelihood Function - Exponential Distribution * Poisson distribution, likelihood ratios (Replies: 0) ... a)What is the likelihood function?. b)What is the mle of t?. 2. Relevant equations. f(x;t)=t*exp(-t*x), E(X)=1/t ,. F(x) = P(X ...
###### Fine-grain Parallelism Using Multi-core, Cell/BE, and GPU Systems: Accelerating the Phylogenetic LikelihoodFunction - IEEE...
We are currently faced with the situation where applications have increasing computational demands and there is a wide selection of parallel processor syst
###### Statistics - log-likelihoodfunction (cross-entropy) [Gerardnico]
The "log-likelihood function" is a probabilistic function. ,MATH, \sum_{i=1}^{N}(1-X_i^i)log(1-Pr[1,B_1^1,B_2^2,\dots,B_k^k])+X ... Statistics - log-likelihood function (cross-entropy). * You are here: *(Statistics,Probability,Machine Learning,Data Mining, ... The "log-likelihood function" is also referred to as the cross-entropy ... data_mining/log_likelihood.txt. · Last modified: 2015/04/13 10:33 by gerardnico. ...
https://gerardnico.com/data_mining/log_likelihood
###### Lesson 4.2 Likelihoodfunction and maximum likelihood - Statistical Inference | Coursera
Lesson 4.2 Likelihood function and maximum likelihood. Para ver esse vídeo, ative o JavaScript e considere fazer upgrade para ... It looks like the same function, but up here this is a function of y given theta. ... Beginning with a binomial likelihood and prior probabilities for simple hypotheses, you will learn how to use Bayes' theorem to ... Lesson 4 takes the frequentist view, demonstrating maximum likelihood estimation and confidence intervals for binomial data. ...
https://pt.coursera.org/lecture/bayesian-statistics/lesson-4-2-likelihood-function-and-maximum-likelihood-9dWnA
###### EUDML | The Exact LikelihoodFunction for a Space Time Model.
... exact likelihood function},. pages = {239-243},. title = {The Exact Likelihood Function for a Space Time Model.},. url = {http ... space time autoregressive moving average models, exact likelihood function. Suggest a Subject Subjects. You must be logged in ... TI - The Exact Likelihood Function for a Space Time Model.. JO - Metrika. PY - 1983. VL - 30. SP - 239. EP - 243. KW - space ... Abraham, B.. "The Exact Likelihood Function for a Space Time Model.." Metrika 30 (1983): 239-243. ,http://eudml.org/doc/175916 ...
https://eudml.org/doc/175916
###### Variants of Hybrid Genetic Algorithms for Optimizing Likelihood ARMA Model Function and Many of Problems | IntechOpen
Variants of Hybrid Genetic Algorithms for Optimizing Likelihood ARMA Model Function and Many of Problems , IntechOpen, ... Variants of Hybrid Genetic Algorithms for Optimizing Likelihood ARMA Model Function and Many of Problems. By Basad Ali Hussain ...
https://www.intechopen.com/books/evolutionary-algorithms/variants-of-hybrid-genetic-algorithms-for-optimizing-likelihood-arma-model-function-and-many-of-prob/
###### LoglikNormalDeltaCens: Log likelihoodfunction to compute mean difference between... in SurvRegCensCov: Weibull Regression for...
Reparametrization of the log likelihood function for a normally distributed censored sample such that the mean difference is a ... parameter of the function, thus allowing to be made inference on. The mean difference is computed as sample 1 - sample 2. ... LoglikWeibullSurvRegCens: Log-likelihood function of a Weibull Survival Regression.... *ParamSampleCens: Maximum Likelihood ... LoglikNormalDeltaCens: Log likelihood function to compute mean difference between... In SurvRegCensCov: Weibull Regression for ...
https://rdrr.io/cran/SurvRegCensCov/man/LoglikNormalDeltaCens.html
###### Choice of similarity measure, likelihoodfunction and parameters for histogram based particle filter tracking in CCTV grey...
It is argued that as long as the likelihood function satisfies certain criteria its analytical form is not critical in the ... The choice of particle filter dissimilarity distance measures and likelihood functions is considered in the context of object ... ORCID: 0000-0001-7195-2509 (2011) Choice of similarity measure, likelihood function and parameters for histogram based particle ... Choice of similarity measure, likelihood function and parameters for histogram based particle filter tracking in CCTV grey ...
http://clok.uclan.ac.uk/3818/
###### Comparisons of Estimators and Tests Based on Modified Likelihood and Message Length Functions - AgEcon Search
A number of modified likelihood and message length functions have been developed for better handling of nuisance parameters but ... In this paper, we empirically compare different modified likelihood and message length functions in the context of estimation ... The true sizes of the Lagrange multiplier tests based on message length functions are rather poor because the score functions ... The results show that estimators based on the conditional profile likelihood and tests based on the marginal likelihood are ...
http://ageconsearch.umn.edu/record/267490
###### Identification of sparse neural functional connectivity using penalized likelihood estimation and basis functions - Semantic...
We further develop an optimization method based on quadratic approximation of the likelihood function for the estimation of ... Model sparsities are achieved by using various penalized likelihood estimations and basis functions. Specifically, we introduce ... A GFAM consists of a set of basis functions convolving the input signals, and a link function generating the firing probability ... The sparse models outperform the full models estimated with the standard maximum likelihood method in out-of-sample predictions ...
https://www.semanticscholar.org/paper/Identification-of-sparse-neural-functional-using-Song-Wang/89f1ab720460423cc82bc695e3293602293ff6da
###### Maximum Likelihood Estimation of Sensor and Action Model Functions on a Mobile Robot
... (2008) ... InProceedings{ICRA08-stronger, title={Maximum Likelihood Estimation of Sensor and Action Model Functions on a Mobile Robot}, ... learn both its action and sensor model functions, starting without an accurate version of either. The resulting algorithm is ...
http://www.cs.utexas.edu/users/ai-lab/pub-view.php?PubID=126624
###### Spatial and temporal dynamics of superspreading events in the 2014-2015 West Africa Ebola epidemic | PNAS
Likelihood Function.. Let E. =. (. E. 1. ,. E. 2. ,. …. ,. E. n. ). be the vector of the exposure/infection times of the n. =. ... as a function of distance d. i. j. between them. Here, we have K. (. d. i. j. ;. η. ). =. e. x. p. (. −. η. d. i. j. ). . After ... Details of the likelihood function and the MCMC algorithm are given in SI Text. Model fit was assessed by comparing the ... Denoting the likelihood by L. (. 𝜽. ;. x. ). , the posterior distribution of 𝜽. is P. (. 𝜽. ,. x. ). ∝. L. (. 𝜽. ;. x. ). π. ( ...
https://www.pnas.org/content/114/9/2337.full
###### Satisfaction as a Function of Perceived Change in Likelihood of Goal Attainment: A Cross-Cultural Study: Media & Communications...
Satisfaction as a Function of Perceived Change in Likelihood of Goal Attainment: A Cross-Cultural Study: 10.4018/978-1-60960- ... "Satisfaction as a Function of Perceived Change in Likelihood of Goal Attainment: A Cross-Cultural Study." In E-Collaboration ... "Satisfaction as a Function of Perceived Change in Likelihood of Goal Attainment: A Cross-Cultural Study." E-Collaboration ... Satisfaction as a Function of Perceived Change in Likelihood of Goal Attainment: A Cross-Cultural Study. Bruce A. Reinig (San ...
https://www.igi-global.com/chapter/satisfaction-function-perceived-change-likelihood/52345
###### Adaptive, locally linear models of complex dynamics | PNAS
3]where the pseudo-log-likelihood function of model parameters θ. a. =. c. →. a. ,. A. a. ,. Σ. a. from X. b. for a Gaussian ... is the maximum-likelihood estimate in X. a. ; l. (. θ. a. ,. X. a. ). −. l. (. θ. c. ,. X. a. ). ≥. 0. ) and also symmetric; ... by the log-likelihood ratio Λ. data. (Eq. 3). To assess significance, we compute the distribution of log-likelihood ratios ... In addition, computing the log-likelihood function in Eq. 4 requires inverting the covariance matrix of the error Σ. Thus, we ...
https://www.pnas.org/content/116/5/1501
###### A comparison of discriminant logistic regression and item response theory likelihood-ratio tests for differential item...
A comparison of discriminant logistic regression and item response theory likelihood-ratio tests for differential item ... functioning (IRTLRDIF) in polytomous short tests/Funcionamiento diferencial del item en tests breves: comparacion entre ... Wang, W. C., & Yeh, Y. L. (2003). Effects of anchor item methods on differential item functioning detection with the likelihood ... Paek, I., & Wilson, M. (2011). Formulating the Rasch Differential Item functioning model under the marginal maximum Likelihood ...
https://www.thefreelibrary.com/A+comparison+of+discriminant+logistic+regression+and+item+response+...-a0455611492
###### Spreading of mood in social networks | Proceedings of the Royal Society of London B: Biological Sciences
Appendix A. Likelihood functions. The following likelihood function was constructed for the development of the 'depressive ... Appendix A outlines the construction of the likelihood functions used in the fitting process. Competing models were assessed ... An equivalent likelihood function was constructed for the 'recovery from depressive symptoms' scenario:. with yk corresponding ... by minimizing the negative log-likelihood -log(L) with respect to p and q using the MATLAB fmincon(). function. Confidence ...
http://rspb.royalsocietypublishing.org/content/282/1813/20151180/
###### TreeBUGS: An R package for hierarchical multinomial-processing-tree modeling | SpringerLink
Likelihood function for the MPT model class. As is implied by their name, MPT models assume a product-multinomial distribution ... The model's likelihood is obtained by plugging these category probabilities into the density function of the product- ... Within the maximum-likelihood framework, researchers usually rely on the likelihood-ratio statistic G 2 to test goodness of fit ... For parameter estimation, this likelihood function is maximized either by general-purpose optimization methods (e.g., gradient ...