MuMIn: Multi-Model Inference

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Model selection and model averaging based on information criteria (AICc and alike).

Author
Kamil Bartoń
Date of publication
2016-01-07 10:42:47
Maintainer
Kamil Bartoń <kamil.barton@go2.pl>
License
GPL-2
Version
1.15.6

View on CRAN

Man pages

AICc
Second-order Akaike Information Criterion
arm.glm
Adaptive Regression by Mixing
data-Beetle
Flour beetle mortality data
data-Cement
Cement hardening data
data-GPA
Grade Point Average data
dredge
Automated model selection
exprApply
Apply a function to calls inside an expression
get.models
Retrieve models from selection table
ICs
Various information criteria
importance
Relative variable importance
manip-formula
Manipulate model formulas
merge.model.selection
Combine model selection tables
model.avg
Model averaging
model.sel
model selection table
model.selection.object
Description of Model Selection Objects
model-utils
Model utility functions
MuMIn-package
Multi-model inference
nested
Identify nested models
par.avg
Parameter averaging
pdredge
Automated model selection using parallel computation
plot
Visualize model selection table
predict.averaging
Predict method for averaged models
QAIC
Quasi AIC or AICc
QIC
QIC and quasi-Likelihood for GEE
r.squaredGLMM
Pseudo-R-squared for Generalized Mixed-Effect models
r.squaredLR
Likelihood-ratio based pseudo-R-squared
std.coef
Standardized model coefficients
stdize
Standardize data
subset.model.selection
Subsetting model selection table
supported-classes
List of supported models
updateable
Make a function return updateable result
Weights
Akaike weights

Files in this package

MuMIn
MuMIn/inst
MuMIn/inst/TODO
MuMIn/tests
MuMIn/tests/classes.R
MuMIn/tests/unmarked.R
MuMIn/tests/parallel.R
MuMIn/tests/misc-tests.R
MuMIn/tests/singularities.R
MuMIn/tests/r_squared_glmm.R
MuMIn/tests/gam-smooth-consitency.R
MuMIn/tests/coxme.R
MuMIn/NAMESPACE
MuMIn/demo
MuMIn/demo/dredge.varying.R
MuMIn/demo/dredge.subset.R
MuMIn/demo/dredge.distsamp.R
MuMIn/demo/gees.R
MuMIn/demo/00Index
MuMIn/demo/pdredge.pcount.R
MuMIn/NEWS
MuMIn/data
MuMIn/data/Beetle.rda
MuMIn/data/Cement.rda
MuMIn/data/GPA.rda
MuMIn/R
MuMIn/R/modify.model.selection.R
MuMIn/R/DIC.R
MuMIn/R/std.coef.R
MuMIn/R/AICc.R
MuMIn/R/ext-mark.R
MuMIn/R/pdredge.R
MuMIn/R/updateable.R
MuMIn/R/coeffs.R
MuMIn/R/predict.R
MuMIn/R/xtable-methods.R
MuMIn/R/dredge.R
MuMIn/R/ICOMP.R
MuMIn/R/getAllTerms.R
MuMIn/R/methods-nobs.R
MuMIn/R/get.models.R
MuMIn/R/r.squaredGLMM.R
MuMIn/R/nested.R
MuMIn/R/plots.R
MuMIn/R/rbind.model.selection.R
MuMIn/R/par.avg.R
MuMIn/R/termdeps.R
MuMIn/R/init.R
MuMIn/R/is.R
MuMIn/R/methods-predict.R
MuMIn/R/ext.R
MuMIn/R/utils-models.R
MuMIn/R/makeArgs.R
MuMIn/R/utils-misc.R
MuMIn/R/coefTable.R
MuMIn/R/quasiLik.R
MuMIn/R/Cp.R
MuMIn/R/model.sel.R
MuMIn/R/methods-logLik.R
MuMIn/R/model.avg.R
MuMIn/R/model.selection.R
MuMIn/R/ext-gamm.R
MuMIn/R/stdize.R
MuMIn/R/r.squaredLR.R
MuMIn/R/importance.R
MuMIn/R/Weights.R
MuMIn/R/arm.glm.R
MuMIn/R/substitution.R
MuMIn/R/formulas.R
MuMIn/MD5
MuMIn/DESCRIPTION
MuMIn/man
MuMIn/man/QAIC.Rd
MuMIn/man/r.squaredLR.Rd
MuMIn/man/dredge.Rd
MuMIn/man/predict.averaging.Rd
MuMIn/man/exprApply.Rd
MuMIn/man/supported-classes.Rd
MuMIn/man/std.coef.Rd
MuMIn/man/data-GPA.Rd
MuMIn/man/model.sel.Rd
MuMIn/man/nested.Rd
MuMIn/man/model.avg.Rd
MuMIn/man/AICc.Rd
MuMIn/man/r.squaredGLMM.Rd
MuMIn/man/QIC.Rd
MuMIn/man/get.models.Rd
MuMIn/man/updateable.Rd
MuMIn/man/merge.model.selection.Rd
MuMIn/man/model.selection.object.Rd
MuMIn/man/stdize.Rd
MuMIn/man/data-Cement.Rd
MuMIn/man/manip-formula.Rd
MuMIn/man/ICs.Rd
MuMIn/man/par.avg.Rd
MuMIn/man/Weights.Rd
MuMIn/man/arm.glm.Rd
MuMIn/man/subset.model.selection.Rd
MuMIn/man/MuMIn-package.Rd
MuMIn/man/data-Beetle.Rd
MuMIn/man/model-utils.Rd
MuMIn/man/pdredge.Rd
MuMIn/man/plot.Rd
MuMIn/man/importance.Rd