AICcmodavg Model selection and multimodel inference based on (Q)AIC(c)
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AICcmodavg Tags

model function model creator inference engine Fuzzy inference system Model-Based Test inference problem variational inference inference model DEVS based system haplotype inference Inference Tool model selection phylogeny inference model selection framework R function model selection table selection table large phylogeny inference statistical inference

AICcmodavg Description

The AICcmodavg package includes functions to create model selection tables based on Akaike's information criterion (AIC) and the second-order AIC (AICc), as well as their quasi-likelihood counterparts (QAIC, QAICc). Tables are printed with delta AIC and Akaike weights. The package also includes functions to conduct model averaging (multimodel inference) for a given parameter of interest or predicted values. Other handy functions enable the computation of relative variable importance, evidence ratios, and confidence sets for the best model. The present version works with linear models ('lm' class), generalized linear models ('glm' class), linear models fit by generalized least squares ('gls' class), linear mixed models ('lme' class), generalized linear mixed models ('mer' class), multinomial and ordinal logistic regressions ('multinom' and 'polr' classes).

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