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*  Logistic model
... may refer to: Logistic function - a continuous sigmoidal curve Logistic map - a discrete version, which exhibits ...
*  Logistic model tree
... s are based on the earlier idea of a model tree: a decision tree that has linear regression models at its ... a logistic model tree (LMT) is a classification model with an associated supervised training algorithm that combines logistic ... Niels Landwehr, Mark Hall, and Eibe Frank (2003). Logistic model trees (PDF). ECML PKDD. CS1 maint: Uses authors parameter ( ... doi:10.1007/s10994-005-0466-3. Sumner, Marc, Eibe Frank, and Mark Hall (2005). Speeding up logistic model tree induction (PDF ...
*  Reverse logistics network modelling
"What is Reverse Logistics?", Reverse Logistics Magazine, Winter/Spring 2006. Fleischmann, Moritz. "Reverse logistics network ... In order to modelling reverse logistics network from an economics point of view, the following simplified reverse logistics ... "Reverse logistics network design: Review of models and solution techniques". academia.edu. Retrieved 3 June 2015. ... According to the introduced model the main differences between forward and reverse logistics can be identified: Uncertainty on ...
*  Sampling (statistics)
CS1 maint: Multiple names: authors list (link) Scott, A.J.; Wild, C.J. (1986). "Fitting logistic models under case-control or ... The model is then built on this biased sample. The effects of the input variables on the target are often estimated with more ... Model Assisted Survey Sampling. CS1 maint: Multiple names: authors list (link) Scheaffer, Richard L., William Mendenhal and R. ... Model Assisted Survey Sampling. CS1 maint: Multiple names: authors list (link) "Voluntary Sampling Method". Lazarsfeld, P., & ...
*  Thérèse Stukel
Her dissertation, supervised by David F. Andrews, was Generalized Logistic Models. She became an assistant professor of ...
*  Probabilistic classification
Some models, such as logistic regression, are conditionally trained: they optimize the conditional probability Pr ( Y , X ) {\ ... For the binary case, a common approach is to apply Platt scaling, which learns a logistic regression model on the scores. An ... Some classification models, such as naive Bayes, logistic regression and multilayer perceptrons (when trained under an ... The former of these is commonly used to train logistic models. A method used to assign scores to pairs of predicted ...
*  Aryldialkylphosphatase
Classen JJ, Engler CR, Kenerley CM, Whittaker AD (April 2000). "A logistic model of subsurface fungal growth with application ... The kinetic model proposed consists of a reversible binding step that takes place between the enzyme and the substrate, and the ... a model organism of the Crenarchaeota". Journal of Bacteriology. 187 (14): 4992-9. doi:10.1128/JB.187.14.4992-4999.2005. PMC ...
*  Population growth
Most populations do not grow exponentially, rather they follow a logistic model. Once the population has reached its carrying ... Mathematical Modeling of Social and Economic Dynamics / Ed. by M. G. Dmitriev and A. P. Petrov, pp. 367-9. Moscow: Russian ... CS1 maint: Multiple names: authors list (link) Korotayev, A. V., & Malkov, A. S. A Compact Mathematical Model of the World ... This analytic solution is useful in analyzing the behavior of population models. In 2017, the estimated annual growth rate was ...
*  Moment closure
"On Approximating the Moments of the Equilibrium Distribution of a Stochastic Logistic Model". Biometrics. 52 (3): 980-991. doi: ... The approximation is particularly useful in models with a very large state space, such as stochastic population models. The ... The approximation has been used successfully to model the spread of the Africanized bee in the Americas and nematode infection ... Marion, G.; Renshaw, E.; Gibson, G. (1998). "Stochastic effects in a model of nematode infection in ruminants". Mathematical ...
*  Rasch model
Specifically, in the original Rasch model, the probability of a correct response is modeled as a logistic function of the ... model with one item parameter. However, rather than being a particular IRT model, proponents of the model regard it as a model ... These variations are available in models such as the two and three parameter logistic models. However, the specification of ... Linacre J.M. (2005). Rasch dichotomous model vs. One-parameter Logistic Model. Rasch Measurement Transactions, 19:3, 1032 Rasch ...
*  Computerized classification test
Jacobs-Cassuto, M.S. (2005). A Comparison of Adaptive Mastery Testing Using Testlets With the 3-Parameter Logistic Model. ... IRT, on the other hand, assumes a trait model; the knowledge or ability measured by the test is a continuum. The classification ... A CCT requires several components: An item bank calibrated with a psychometric model selected by the test designer A starting ... Frick, T. W. (1990). A comparison of three decisions models for adapting the length of computer-based mastery tests. Journal of ...
*  Multinomial logistic regression
The multinomial logistic model also assumes that the dependent variable cannot be perfectly predicted from the independent ... Logistic} (0,1)} then b X ∼ Logistic ⁡ ( 0 , b ) . {\displaystyle bX\sim \operatorname {Logistic} (0,b).} This means that the ... The formulation of binary logistic regression as a log-linear model can be directly extended to multi-way regression. That is, ... It is also possible to formulate multinomial logistic regression as a latent variable model, following the two-way latent ...
*  Psychological statistics
They are one parameter logistic model, two parameter logistic model and three parameter logistic model. In addition, ... Multi-level modeling; Survival-Failure analysis; Structural Equations Modeling; hierarchical linear modelling etc. are very ... The modern test theory is based on latent trait model. Every item estimates the ability of the test taker. The ability ... Loehlin, J. E. (1992). Latent Variable Models: An Introduction to Factor, Path, and Structural Analysis (2nd ed.). Hillsdale, ...
*  Quantitative linguistics
The Piotrowski law is a case of the so-called logistic model (cf. logistic equation). It was shown that it covers also language ... One of the central assumptions of QL is that some laws (e.g. the distribution of word lengths) require different models, at ... Since George Kingsley Zipf (the well-known "Zipf's Law"), a large number of mathematical models of the relation between rank ... abide by a law known in QL as Piotrowski law, and corresponds to growth models in other scientific disciplines. ...
*  Late-life mortality deceleration
... can be modeled via modifications of the Gompertz law, using various logistic models. The rates ... and models have incorporated it. It has been criticized at times, and recently has been very seriously criticized; see below. ... "Note on Some Mathematical Mortality Models", in E. W. Wolstenholme and M. O. O'Connor, The Lifespan of Animals, Boston: Little ...
*  Generalized linear model
Such a model is a log-odds or logistic model. Generalized linear models cover all these situations by allowing for response ... The resulting model is known as logistic regression (or multinomial logistic regression in the case that K-way rather than ... Such a model is termed an exponential-response model (or log-linear model, since the logarithm of the response is predicted to ... GLMs with this setup are logistic regression models (or logit models). Alternatively, the inverse of any continuous cumulative ...
*  LogitBoost
Specifically, if one considers AdaBoost as a generalized additive model and then applies the cost functional of logistic ... Specifically, given that we seek an additive model of the form f = ∑ t α t h t {\displaystyle f=\sum _{t}\alpha _{t}h_{t}} the ... http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.51.9525 Gradient boosting Logistic model tree. ... Additive logistic regression: a statistical view of boosting. Annals of Statistics 28(2), 2000. 337-407. ...
*  Logit
In plant disease epidemiology the logit is used to fit the data to a logistic model. With the Gompertz and Monomolecular models ... Hilbe, Joseph M. (2009), Logistic Regression Models, CRC Press, p. 3, ISBN 9781420075779 . Cramer, J. S. (2003), Logit Models ... The logit in logistic regression is a special case of a link function in a generalized linear model: it is the canonical link ... The "logistic" function of any number α {\displaystyle \alpha } is given by the inverse-logit: logit − 1 ⁡ ( α ) = logistic ...
*  Routine activity theory
A hierarchical logistic model analysis across Seattle neighborhoods. Criminology, 32(3), 387-414. Smith, W. R., Frazee, S. G ... Criminologist Lynch (1987), using "domain-specific" models, demonstrates that occupation-related activities generally have a ... Garofalo, J. (1987). Reassessing the lifestyle model of criminal victimization. Beverly Hills, California: Sage. Maxfield, ...
*  Delivery drone
FedEx is reported to be testing integration of drone delivery with their existing logistics model. In May 2015, CJ Express ... postal companies have been forced to seek new ways to yond their traditional letter delivery business models. Different postal ... ". "SF-Express Logistics UAV by XAIRCRAFT". FPS Distribution Press Release (13 March 2015) First UK Commercial Delivery with ...
*  Anton Formann
As a senior author, Formann also showed that the common assumption that the EM estimation of the two-parameter logistic model ... He showed that subjects and tasks can be arrayed on a unidimensional scale and, by employing the linear logistic test model, ... Formann was probably the first researcher to practically apply Fischer's linear logistic test model (LLTM) for test development ... Preinerstorfer, D., & Formann, A. K. (2012). Parameter recovery and model selection in mixed Rasch models. British Journal of ...
*  Jane M. Olson
She later developed the conditional logistic model for studying linkage from a sample of affected relative pairs. This model ... There she "developed statistical methods for model-free genetic linkage analysis". She subsequently became involved in the ...
*  Hosmer-Lemeshow test
The expected number (from the logistic model) can be calculated using the equation from the logistic regression. These are ... The current model is P(success) vs caffeine, and appears to be an inadequate model. A better model might be P(success) vs ... The expected probability of success (a grade of A) is given by the equation for the logistic regression model: p ( s u c c e s ... Logistic regression models provide an estimate of the probability of an outcome, usually designated as a "success". It is ...
*  The Net Holding
"The Net Holding in 2015: Introducing New Logistics Models for The Middle East". Marcopolis. November 3, 2015. "About Us". The ... The second division, Net Logistics is a freight forwarder and contract logistics company which covers several industries in six ... In Beirut, The Net Logistics took advantage of the Beirut Port Free Trade, and opened a big warehouse in the area in 2007. The ... It provides international express, freight-forwarding services as a logistics group from its offices in Middle East. The Net ...
*  Linear discriminant analysis
Hilbe, J. M. (2009). Logistic Regression Models. Chapman & Hall/CRC Press. ISBN 978-1-4200-7575-5. Mika, S.; et al. (1999). " ... Edward Altman's 1968 model is still a leading model in practical applications. In computerised face recognition, each face is ... Logistic regression or other methods are now more commonly used. The use of discriminant analysis in marketing can be described ... LDA explicitly attempts to model the difference between the classes of data. PCA on the other hand does not take into account ...
*  Veterans benefits for post-traumatic stress disorder in the United States
In 1917, the U.S. Congress passed legislation emphasizing an indemnity model for veterans disability benefits. Congress sought ... the companies with current VBA contracts are Logistics Health, Inc. (LHI); Veterans Evaluation Services (VES); QTC (QTC in turn ...