AICcmodavg (version 1.17)
Model selection and multimodel inference based on (Q)AIC(c)
Description
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 features functions to
conduct classic model averaging (multimodel inference) for a
given parameter of interest or predicted values, as well as a
shrinkage version of model averaging parameter estimates.
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), and nonlinear models ('nls'
class). The package also supports various models incorporating
detection probabilities such as single-season occupancy models
('unmarkedFitOccu' class), multiple-season occupancy models
('unmarkedFitColExt' class), single-season heterogeneity models
('unmarkedFitOccuRN' class), and single-season and
multiple-season N-mixture models for repeated counts
('unmarkedFitPCount' and 'unmarkedFitPCO' classes,
respectively).
