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MuMIn (version 1.15.6)

Multi-Model Inference

Description

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

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Version

Install

install.packages('MuMIn')

Monthly Downloads

16,303

Version

1.15.6

License

GPL-2

Maintainer

Kamil Barto

Last Published

January 7th, 2016

Functions in MuMIn (1.15.6)

AICc

Second-order Akaike Information Criterion

Beetle

Flour beetle mortality data

arm.glm

Adaptive Regression by Mixing

Weights

Akaike weights

Cement

Cement hardening data

nested

Identify nested models

model.sel

model selection table

model.avg

Model averaging

plot.model.selection

Visualize model selection table

exprApply

Apply a function to calls inside an expression

model.selection.object

Description of Model Selection Objects

merge.model.selection

Combine model selection tables

Information criteria

Various information criteria

predict.averaging

Predict method for averaged models

MuMIn-package

Multi-model inference

QIC

QIC and quasi-Likelihood for GEE

updateable

Make a function return updateable result

get.models

Retrieve models from selection table

stdize

Standardize data

Formula manipulation

Manipulate model formulas

importance

Relative variable importance

par.avg

Parameter averaging

GPA

Grade Point Average data

pdredge

Automated model selection using parallel computation

QAIC

Quasi AIC or AICc

dredge

Automated model selection

Model utilities

Model utility functions

r.squaredGLMM

Pseudo-R-squared for Generalized Mixed-Effect models

std.coef

Standardized model coefficients

r.squaredLR

Likelihood-ratio based pseudo-R-squared

MuMIn-models

List of supported models

subset.model.selection

Subsetting model selection table