Search results for "Penalized Weighted Residual Sum of Squares."

showing 2 items of 2 documents

A graphical model selection tool for mixed models

2017

Model selection can be defined as the task of estimating the performance of different models in order to choose the most parsimonious one, among a potentially very large set of candidate statistical models. We propose a graphical representation to be considered as an extension to the class of mixed models of the deviance plot proposed in the literature within the framework of classical and generalized linear models. This graphical representation allows, once a reduced number of models have been selected, to identify important covariates focusing only on the fixed effects component, assuming the random part properly specified. Nevertheless, we suggest also a standalone figure representing th…

0301 basic medicineStatistics and ProbabilityMixed modelModel selectionFeature selection01 natural sciencesTask (project management)Deviance plot Penalized Weighted Residual Sum of Squares Variable selection010104 statistics & probability03 medical and health sciences030104 developmental biologyModeling and SimulationStatisticsGraphical model0101 mathematicsSelection (genetic algorithm)Mathematics
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Model interpretation from the additive elements of the PWRSS in GLMMs

2013

Generalized Linear Mixed models(GLMMs)have rapidly become a widely used tool for modelling clustered and longitudinal data with non-Normal responses. Although a large amount of work has been done in the literature on likelihood-based inference on GLMMs,little seems to have been done on the decomposition of the total variability associated to the different components of a mixed model.In this work we try to generalize the idea of likelihood additive elements Whittaker,1984), proposed in the context of GLMs,to the case of GLMMs by using the Penalized Weighted Residual Sum of Squares(PWRSS). The proposal is illustrated by means of areal application.

Additive elementPenalized Weighted Residual Sum of Squares.Settore SECS-S/01 - StatisticaGLMM
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