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glmm (version 1.4.3)

Generalized Linear Mixed Models via Monte Carlo Likelihood Approximation

Description

Approximates the likelihood of a generalized linear mixed model using Monte Carlo likelihood approximation. Then maximizes the likelihood approximation to return maximum likelihood estimates, observed Fisher information, and other model information.

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Version

Install

install.packages('glmm')

Monthly Downloads

898

Version

1.4.3

License

GPL-2

Maintainer

Christina Knudson

Last Published

April 7th, 2022

Functions in glmm (1.4.3)

BoothHobert

A Logit-Normal GLMM Dataset from Booth and Hobert
cbpp2

Contagious Bovine Pleuropneumonia
logLik.glmm

Monte Carlo Log Likelihood
confint.glmm

Calculates Asymptotic Confidence Intervals
Booth2

A Logit-Normal GLMM Dataset
coef.glmm

Extract Model Coefficients
glmm

Fitting Generalized Linear Mixed Models using MCML
se

Standard Error
binomial.glmm

Functions for the Binomial family.
mcse

Monte Carlo Standard Error
bernoulli.glmm

Functions for the Bernoulli family.
bacteria

Presence of Bacteria after Drug Treatments
radish2

Radish count data set
mcvcov

Monte Carlo Variance Covariance Matrix
salamander

Salamander mating data set from McCullagh and Nelder (1989)
poisson.glmm

Functions for the Poisson family.
murder

Number of Homicide Victims Known
vcov.glmm

Variance-Covariance Matrix
varcomps

Extract Model Variance Components
summary.glmm

Summarizing GLMM Fits