Package: cAIC4 1.0
cAIC4: Conditional Akaike Information Criterion for 'lme4' and 'nlme'
Provides functions for the estimation of the conditional Akaike information in generalized mixed-effect models fitted with (g)lmer() from 'lme4', lme() from 'nlme' and gamm() from 'mgcv'. For a manual on how to use 'cAIC4', see Saefken et al. (2021) <doi:10.18637/jss.v099.i08>.
Authors:
cAIC4_1.0.tar.gz
cAIC4_1.0.zip(r-4.5)cAIC4_1.0.zip(r-4.4)cAIC4_1.0.zip(r-4.3)
cAIC4_1.0.tgz(r-4.4-any)cAIC4_1.0.tgz(r-4.3-any)
cAIC4_1.0.tar.gz(r-4.5-noble)cAIC4_1.0.tar.gz(r-4.4-noble)
cAIC4_1.0.tgz(r-4.4-emscripten)cAIC4_1.0.tgz(r-4.3-emscripten)
cAIC4.pdf |cAIC4.html✨
cAIC4/json (API)
| # Install 'cAIC4' in R: |
| install.packages('cAIC4', repos = c('https://druegamer.r-universe.dev', 'https://cloud.r-project.org')) |
- Zambia - Subset of the Zambia data set on childhood malnutrition
- guWahbaData - Data from Gu and Wahba
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 3 years agofrom:ec9cd4b045. Checks:OK: 1 NOTE: 6. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Nov 20 2024 |
| R-4.5-win | NOTE | Nov 20 2024 |
| R-4.5-linux | NOTE | Nov 20 2024 |
| R-4.4-win | NOTE | Nov 20 2024 |
| R-4.4-mac | NOTE | Nov 20 2024 |
| R-4.3-win | NOTE | Nov 20 2024 |
| R-4.3-mac | NOTE | Nov 20 2024 |
Exports:anocAICcAICdeleteZeroComponentsgetcondLLgetWeightsmodelAvgpredictMAstepcAICsummaryMA
Dependencies:bootlatticelme4MASSMatrixmgcvminqamvtnormnlmenloptrRcppRcppEigenRLRsim
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Conditional Akaike Information Criterion for 'lme4' and 'nlme' | cAIC4-package cAIC4 |
| Comparison of several lmer objects via cAIC | anocAIC |
| Conditional Akaike Information for 'lme4' and 'lme' | cAIC |
| Delete random effect terms with zero variance | deleteZeroComponents deleteZeroComponents.lme deleteZeroComponents.merMod |
| Function to calculate the conditional log-likelihood | getcondLL getcondLL.lme getcondLL.merMod |
| Optimize weights for model averaging. | getWeights |
| Data from Gu and Wahba (1991) | guWahbaData |
| Model Averaging for Linear Mixed Models | modelAvg |
| Prediction of model averaged linear mixed models | predictMA |
| Print method for cAIC | print.cAIC |
| 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. | stepcAIC |
| Summary of model averaged linear mixed models | summaryMA |
| Subset of the Zambia data set on childhood malnutrition | Zambia |
