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glmm (version 1.4.5)

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

973

Version

1.4.5

License

GPL-2

Maintainer

Christina Knudson

Last Published

September 22nd, 2024

Functions in glmm (1.4.5)

mcvcov

Monte Carlo Variance Covariance Matrix
vcov.glmm

Variance-Covariance Matrix
se

Standard Error
summary.glmm

Summarizing GLMM Fits
Booth2

A Logit-Normal GLMM Dataset
bacteria

Presence of Bacteria after Drug Treatments
cbpp2

Contagious Bovine Pleuropneumonia
varcomps

Extract Model Variance Components
radish2

Radish count data set
binomial.glmm

Functions for the Binomial family.
logLik.glmm

Monte Carlo Log Likelihood
poisson.glmm

Functions for the Poisson family.
confint.glmm

Calculates Asymptotic Confidence Intervals
BoothHobert

A Logit-Normal GLMM Dataset from Booth and Hobert
salamander

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

Functions for the Bernoulli family.
glmm

Fitting Generalized Linear Mixed Models using MCML
coef.glmm

Extract Model Coefficients
murder

Number of Homicide Victims Known
mcse

Monte Carlo Standard Error