cAIC4-package {cAIC4} | R Documentation |
Provides functions for the estimation of the conditional Akaike information in generalized mixed-effect models fitted with (g)lmer() from 'lme4'.
The DESCRIPTION file:
Package: | cAIC4 |
Type: | Package |
Title: | Conditional Akaike Information Criterion for 'lme4' |
Version: | 0.8 |
Date: | 2019-04-17 |
Author: | Benjamin Saefken and David Ruegamer, with contributions from Sonja Greven and Thomas Kneib |
Maintainer: | David Ruegamer <david.ruegamer@gmail.com> |
Depends: | lme4(>= 1.1-6), methods, Matrix, stats4 |
Suggests: | gamm4, mgcv |
Description: | Provides functions for the estimation of the conditional Akaike information in generalized mixed-effect models fitted with (g)lmer() from 'lme4'. |
License: | GPL (>= 2) |
Packaged: | 2019-02-01 22:44:08 UTC; david |
NeedsCompilation: | no |
Date/Publication: | 2014-08-12 11:48:10 |
RoxygenNote: | 6.1.1 |
Index of help topics:
Zambia Subset of the Zambia data set on childhood malnutrition anocAIC Comparison of several lmer objects via cAIC cAIC Conditional Akaike Information for 'lme4' cAIC4-package Conditional Akaike Information Criterion for 'lme4' deleteZeroComponents Delete random effect terms with zero variance getcondLL Function to calculate the conditional log-likelihood guWahbaData Data from Gu and Wahba (1991) print.cAIC Print method for cAIC stepcAIC Function to stepwise select the (generalized) linear mixed model fitted via (g)lmer() or (generalized) additive (mixed) model fitted via gamm4() with the smallest cAIC.
Benjamin Saefken and David Ruegamer, with contributions from Sonja Greven and Thomas Kneib
Maintainer: David Ruegamer <david.ruegamer@gmail.com>
Saefken, B., Kneib T., van Waveren C.-S. and Greven, S. (2014) A unifying approach to the estimation of the conditional Akaike information in generalized linear mixed models. Electronic Journal Statistics Vol. 8, 201-225.
Greven, S. and Kneib T. (2010) On the behaviour of marginal and conditional AIC in linear mixed models. Biometrika 97(4), 773-789.
Efron , B. (2004) The estimation of prediction error. J. Amer. Statist. Ass. 99(467), 619-632.
b <- lmer(Reaction ~ Days + (Days | Subject), sleepstudy) cAIC(b)