selMod {pgirmess}R Documentation

Model selection according to information theoretic methods

Description

Handles lm, glm and list of e.g. lm, glm, nls, lme and nlme objects and provides parameters to compare models according to Anderson et al. (2001)

Usage

    selMod(aModel, Order = "AICc", ...)

    ## S3 method for class 'lm':
    selMod(aModel, Order = "AICc", dropNull = FALSE, selconv=TRUE, ...)
    ## S3 method for class 'list':
    selMod(aModel, Order = "AICc", ...)

Arguments

aModel a lm or glm model or a list of relevant models (see details)
dropNull if TRUE, drops the simplest model (e.g. y~1)
Order if set to "AICc" (default) sort the models on this parameter, otherwise "AIC" is allowed
selconv if TRUE (default) keep the models for which convergence is obtained (glm object only) and with no anova singularity (lm and glm)
... other parameters to be passed as arguments (not used here)

Details

This function provides parameters used in the information theoretic methods for model comparisons.

Value

A dataframe including:

LL the maximized log-likelihood
K the number of estimated parameters
N2K the number of observations/K
AIC the Akaike index criterion
deltAIC the difference between AIC and the lowest AIC value
w_i the Akaike weights
deltAICc the difference between AICc and the lowest AICc value; advised to be used when n2K < 40
w_ic the AICc weights


The models examined from first to last are stored as attribute

Author(s)

Patrick Giraudoux and David Pleydell: pgiraudo@univ-fcomte.fr, dpleydel@univ-fcomte.fr

References

See Also

AIC,logLik

Examples

 library(MASS)
 anorex.1 <- lm(Postwt ~ Prewt*Treat, data = anorexia)
 selMod(anorex.1)
 anorex.2 <- glm(Postwt ~ Prewt*Treat, family=gaussian,data = anorexia)
 selMod(anorex.2)
 anorex.3<-lm(Postwt ~ Prewt+Treat, data = anorexia)
 mycomp<-selMod(list(anorex.1,anorex.2,anorex.3))
 mycomp
 attributes(mycomp)$models

[Package pgirmess version 1.3.7 Index]