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glmm (version 1.4.4)

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

531

Version

1.4.4

License

GPL-2

Maintainer

Christina Knudson

Last Published

October 9th, 2022

Functions in glmm (1.4.4)

se

Standard Error
summary.glmm

Summarizing GLMM Fits
poisson.glmm

Functions for the Poisson family.
varcomps

Extract Model Variance Components
radish2

Radish count data set
murder

Number of Homicide Victims Known
mcvcov

Monte Carlo Variance Covariance Matrix
mcse

Monte Carlo Standard Error
salamander

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

Variance-Covariance Matrix
binomial.glmm

Functions for the Binomial family.
cbpp2

Contagious Bovine Pleuropneumonia
bacteria

Presence of Bacteria after Drug Treatments
bernoulli.glmm

Functions for the Bernoulli family.
coef.glmm

Extract Model Coefficients
confint.glmm

Calculates Asymptotic Confidence Intervals
glmm

Fitting Generalized Linear Mixed Models using MCML
logLik.glmm

Monte Carlo Log Likelihood
Booth2

A Logit-Normal GLMM Dataset
BoothHobert

A Logit-Normal GLMM Dataset from Booth and Hobert