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

This 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 mixed models ('lme' class), multinomial and ordinal logistic regressions ('multinom' and 'polr' classes).

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