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AICcmodavg (version 2.3-2)

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

7,218

Version

2.3-2

License

GPL (>= 2)

Maintainer

Marc J Mazerolle

Last Published

March 20th, 2023

Functions in AICcmodavg (2.3-2)

Likelihood-Ratio Test Corrected for Overdispersion

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

Flour Beetle Data

Computing AIC, AICc, QAIC, and QAICc

AICcmodavg-defunct

Defunct Functions in AICcmodavg Package

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

AICcmodavg-package

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

Create Model Selection Tables

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

Identify Parameters with Large Standard Errors

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

Bullfrog Occupancy and Common Reed Invasion

Blood Calcium Concentration in Birds

Check Convergence of Fitted Model

Heat Expended Following Hardening of Portland Cement

Compute Model Selection Relative Frequencies

Compute Covariance Diagnostic for Lambda in N-mixture Models

Computing Confidence Set for the Kullback-Leibler Best Model

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

Create Model Selection Tables Based on BIC

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

Compute Summary Statistics from Detection Histories

Habitat Preference of Lizards

Compute Summary Statistics from Distance Sampling Data

Compute Summary Statistics from Time to Detection Data

Compute Condition Number

Fat Data and Body Measurements

GPA Data and Standardized Test Scores

Create Model Selection Tables based on Multiple Comparisons

Extract Distribution Family and Link Function

Newt Capture-mark-recapture Data

Create Model Selection Tables from Bayesian Analyses

Extract Log-Likelihood of Model

Frog Dehydration Experiment on Three Substrate Types

Iron Content in Food

Compute Importance Values of Variable

Create Model Selection Tables from User-supplied Information Criterion

Compute Summary Statistics from Count Histories

Compute Evidence Ratio Between Two Models

Extract SE of Fixed Effects

Salamander Capture-mark-recapture Data

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

Anuran Larvae Counts in Minnow Traps Across Pond Type

Compute Model-averaged Parameter Estimate (Multimodel Inference)

Gopher Tortoise Distance Sampling Data

Computing BIC or QBIC

Display Model Summary Corrected for Overdispersion

Compute Model-averaged Predictions

Various Utility Functions

Turkey Weight Gain

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

Extract Predictors from Candidate Model List

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

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

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

Format Objects to LaTeX or HTML

Computing Predicted Values and Standard Errors

Custom Computation of BIC and QBIC from User-supplied Input