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AICcmodavg (version 2.1-1)

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' and 'rjags' 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

9,684

Version

2.1-1

License

GPL (>= 2)

Maintainer

Marc J Mazerolle

Last Published

June 19th, 2017

Functions in AICcmodavg (2.1-1)

Create Model Selection Tables

Custom Creation of Model Selection Tables from User-supplied Input Based on (Q)AIC(c)

AICcmodavg-defunct

Defunct Functions in AICcmodavg Package

AICcmodavg-package

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

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

Computing AIC, AICc, QAIC, and QAICc

Custom Computation of AIC, AICc, QAIC, and QAICc from User-supplied Input

Flour Beetle Data

Create Model Selection Tables Based on BIC

Check Convergence of Fitted Model

Identify Parameters with Large Standard Errors

Bullfrog Occupancy and Common Reed Invasion

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

Computing Confidence Set for the Kullback-Leibler Best Model

Compute Summary Statistics from Distance Sampling Data

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

Extract Predictors from Candidate Model List

Blood Calcium Concentration in Birds

Heat Expended Following Hardening of Portland Cement

Frog Dehydration Experiment on Three Substrate Types

Compute Evidence Ratio Between Two Models

GPA Data and Standardized Test Scores

Compute Importance Values of Variable

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

Computing Predicted Values and Standard Errors

Extract Distribution Family and Link Function

Fat Data and Body Measurements

Salamander Capture-mark-recapture Data

Gopher Tortoise Distance Sampling Data

Compute Summary Statistics from Detection Histories

Create Model Selection Tables from Bayesian Analyses

Iron Content in Food

Habitat Preference of Lizards

Compute Model-averaged Predictions

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

Custom Computation of BIC and QBIC from User-supplied Input

Custom Creation of Model Selection Tables from User-supplied Input Based on (Q)BIC

Compute Model Selection Relative Frequencies

Compute Summary Statistics from Count Histories

Format Objects to LaTeX or HTML

Compute Covariance Diagnostic for Lambda in N-mixture Models

Various Utility Functions

Create Model Selection Tables based on Multiple Comparisons

Compute Condition Number

Extract Log-Likelihood of Model

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

Anuran Larvae Counts in Minnow Traps Across Pond Type

Compute Model-averaged Parameter Estimate (Multimodel Inference) from User-supplied Input

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

Compute Model-averaged Parameter Estimate (Multimodel Inference)

Newt Capture-mark-recapture Data

Turkey Weight Gain

Computing BIC or QBIC