Learn R Programming

⚠️There's a newer version (0.2.3) of this package.Take me there.

glmmsr (version 0.1.0)

Fit a Generalized Linear Mixed Model

Description

Conduct inference about generalized linear mixed models, with a choice about which method to use to approximate the likelihood. In addition to the Laplace and adaptive Gaussian quadrature approximations, which are borrowed from 'lme4', the likelihood may be approximated by the sequential reduction approximation, or an importance sampling approximation. These methods provide an accurate approximation to the likelihood in some situations where it is not possible to use adaptive Gaussian quadrature.

Copy Link

Version

Install

install.packages('glmmsr')

Monthly Downloads

11

Version

0.1.0

License

GPL (>= 2)

Issues

Pull Requests

Stars

Forks

Maintainer

Helen Ogden

Last Published

March 9th, 2016

Functions in glmmsr (0.1.0)

glmmFit

Construct a glmmFit object
find_approximation_name

Find the name of the likelihood approximation used for fitting
print.glmmFit

Print glmmFit object
three_level

A dataset simulated from a three-level model
continuous_beliefs

A vector of terms in the factorization of a graphical model, of mixed continuous types.
cluster_graph

The beliefs for the clusters and sepsets of a cluster tree, of mixed continuous types.
optimize_glmm

Maximize the approximated log-likelihood
glmmsr

glmmsr: fit GLMMs with various approximation methods
two_level

A dataset simulated from a two-level model
find_modfr_glmm

Parse a formula (and possibly subformulas)
calibration_parameters

Parameters needed to calibrate the cluster tree
summaryGlmmFit

Construct a summaryGlmmFit object
print.summaryGlmmFit

Print summaryGlmmFit object
find_lfun_glmm

Find the log-likelihood function
summary.glmmFit

Summarize a glmmFit object
glmm

Fit a GLMM