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AICcmodavg (version 2.2-1)

Model Selection and Multimodel Inference Based on (Q)AIC(c)

Description

Functions to implement model selection and multimodel inference based on Akaike's information criterion (AIC) and the second-order AIC (AICc), as well as their quasi-likelihood counterparts (QAIC, QAICc) from various model object classes. The package implements classic model averaging for a given parameter of interest or predicted values, as well as a shrinkage version of model averaging parameter estimates or effect sizes. The package includes diagnostics and goodness-of-fit statistics for certain model types including those of 'unmarkedFit' classes estimating demographic parameters after accounting for imperfect detection probabilities. Some functions also allow the creation of model selection tables for Bayesian models of the 'bugs', 'rjags', and 'jagsUI' classes. Functions also implement model selection using BIC. Objects following model selection and multimodel inference can be formatted to LaTeX using 'xtable' methods included in the package.

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Version

Install

install.packages('AICcmodavg')

Monthly Downloads

7,288

Version

2.2-1

License

GPL (>= 2)

Maintainer

Marc J Mazerolle

Last Published

March 8th, 2019

Functions in AICcmodavg (2.2-1)

AICcmodavg-defunct

Defunct Functions in AICcmodavg Package

Create Model Selection Tables from User-supplied Input Based on (Q)AIC(c)

Create Model Selection Tables

Frog Dehydration Experiment on Three Substrate Types

Compute Model Selection Relative Frequencies

Iron Content in Food

Habitat Preference of Lizards

Create Model Selection Tables from Bayesian Analyses

Compute Model-averaged Parameter Estimate with Shrinkage (Multimodel Inference)

Bullfrog Occupancy and Common Reed Invasion

Computing AIC, AICc, QAIC, and QAICc

Blood Calcium Concentration in Birds

Compute Summary Statistics from Distance Sampling Data

Create Model Selection Tables Based on BIC

Create Model Selection Tables from User-supplied Input Based on (Q)BIC

Extract Log-Likelihood of Model

Compute AIC, AICc, QAIC, and QAICc from User-supplied Input

Extract SE of Fixed Effects of coxme, glmer, and lmekin Fit

Create Model Selection Tables from User-supplied Information Criterion

Newt Capture-mark-recapture Data

Compute Importance Values of Variable

Create Model Selection Tables based on Multiple Comparisons

Identify Parameters with Large Standard Errors

Custom Computation of BIC and QBIC from User-supplied Input

Compute Summary Statistics from Count Histories

Strength of Pine Wood Based on the Density Adjusted for Resin Content

Computing Confidence Set for the Kullback-Leibler Best Model

Compute MacKenzie and Bailey Goodness-of-fit Test for Single Season, Dynamic, and Royle-Nichols Occupancy Models

Compute Evidence Ratio Between Two Models

Format Objects to LaTeX or HTML

Anuran Larvae Counts in Minnow Traps Across Pond Type

Fat Data and Body Measurements

Compute Condition Number

GPA Data and Standardized Test Scores

Heat Expended Following Hardening of Portland Cement

Compute Model-averaged Parameter Estimate (Multimodel Inference)

Check Convergence of Fitted Model

Various Utility Functions

Compute Covariance Diagnostic for Lambda in N-mixture Models

Extract Predictors from Candidate Model List

Compute Summary Statistics from Detection Histories

Extract Distribution Family and Link Function

Turkey Weight Gain

Compute Model-averaged Parameter Estimate from User-supplied Information Criterion

Computing BIC or QBIC

Compute Model-averaged Parameter Estimate from User-supplied Input Based on (Q)AIC(c)

Compute Model-averaged Effect Sizes (Multimodel Inference on Group Differences)

Computing Predicted Values and Standard Errors

Compute Model-averaged Predictions

Display Model Summary Corrected for Overdispersion

Gopher Tortoise Distance Sampling Data

Salamander Capture-mark-recapture Data

Flour Beetle Data

Likelihood-Ratio Test Corrected for Overdispersion

Compute Chi-square Goodness-of-fit Test for N-mixture Models

AICcmodavg-package

Model Selection and Multimodel Inference Based on (Q)AIC(c)

Estimate Dispersion for Poisson and Binomial GLM's and GLMM's