R: Multi-Model Inference

# Multi-Model Inference

## Documentation for package ‘MuMIn’ version 1.47.5

- DESCRIPTION file.
- Code demos. Use demo() to run them.
- Package NEWS.

## Help Pages

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 minimal variance model weights
bootWeights | Bootstrap model weights
CAICF | Various information criteria
Cement | Cement hardening data
coeffs | Model utility functions
coefplot | Plot model coefficients
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.averaging | Plot model coefficients
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