Multi-Model Inference

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Documentation for package ‘MuMIn’ version 1.43.9

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MuMIn-package Multi-model inference
AICc Second-order Akaike Information Criterion
append.model.selection Combine model selection tables
arm.glm Adaptive Regression by Mixing
armWeights Adaptive Regression by Mixing
Beetle Flour beetle mortality data
beta.weights Standardized model coefficients
BGWeights Bates-Granger model weights
bootWeights Bootstrap model weights
CAICF Various information criteria
Cement Cement hardening data
coeffs Model utility functions
coefTable Model utility functions
coefTable.averaging Model utility functions
coefTable.default Model utility functions
coefTable.gee Model utility functions
coefTable.lme Model utility functions
cos2Weights Cos-squared model weights
Cp Various information criteria
dc Automated model selection
DIC Various information criteria
dredge Automated model selection
expand.formula Manipulate model formulas
exprApply Apply a function to calls inside an expression
gamm-wrapper Make a function return updateable result
get.models Retrieve models from selection table
get.response Model utility functions
getAllTerms Model utility functions
getAllTerms.terms Model utility functions
get_call Make a function return updateable result
GPA Grade Point Average data
has Subsetting model selection table
IC Various information criteria
ICOMP Various information criteria
importance Per-variable sum of model weights
jackknifeWeights Jackknifed model weights
loo Leave-one-out cross-validation
loo.default Leave-one-out cross-validation
loo.lm Leave-one-out cross-validation
Mallows' Cp Various information criteria
merge.model.selection Combine model selection tables
mod.sel model selection table
model.avg Model averaging
model.avg.default Model averaging
model.avg.model.selection Model averaging
model.names Model utility functions
model.sel model selection table
model.sel.default model selection table
model.sel.model.selection model selection table
model.selection.object Description of Model Selection Objects
MuMIn Multi-model inference
MuMIn-gamm Make a function return updateable result
MuMIn-model-utils Model utility functions
MuMIn-models List of supported models
nested Identify nested models
null.fit Likelihood-ratio based pseudo-R-squared
par.avg Parameter averaging
partial.sd Standardized model coefficients
pdredge Automated model selection using parallel computation
pget.models Retrieve models from selection table
plot.model.selection Visualize model selection table
predict.averaging Predict method for averaged models
print.averaging Model averaging
print.model.selection Automated model selection
QAIC Quasi AIC or AICc
QAICc Quasi AIC or AICc
QIC QIC and quasi-Likelihood for GEE
QICu QIC and quasi-Likelihood for GEE
quasiLik QIC and quasi-Likelihood for GEE
r.squaredGLMM Pseudo-R-squared for Generalized Mixed-Effect models
r.squaredGLMM.merMod Pseudo-R-squared for Generalized Mixed-Effect models
r.squaredLR Likelihood-ratio based pseudo-R-squared
rbind.model.selection Combine model selection tables
simplify.formula Manipulate model formulas
stackingWeights Stacking model weights
std.coef Standardized model coefficients
stdize Standardize data
stdize.data.frame Standardize data
stdize.default Standardize data
stdize.formula Standardize data
stdize.logical Standardize data
stdizeFit Standardize data
subset.model.selection Subsetting model selection table
sum.of.weights Per-variable sum of model weights
sw Per-variable sum of model weights
tTable Model utility functions
uGamm Make a function return updateable result
updateable Make a function return updateable result
updateable2 Make a function return updateable result
V Automated model selection
Weights Akaike weights
Weights<- Akaike weights
[.model.selection Subsetting model selection table
[[.model.selection Subsetting model selection table