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glmmrBase (version 0.4.6)

Generalised Linear Mixed Models in R

Description

Specification, analysis, simulation, and fitting of generalised linear mixed models. Includes Markov Chain Monte Carlo Maximum likelihood and Laplace approximation model fitting for a range of models, non-linear fixed effect specifications, a wide range of flexible covariance functions that can be combined arbitrarily, robust and bias-corrected standard error estimation, power calculation, data simulation, and more. See for a detailed manual.

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Install

install.packages('glmmrBase')

Monthly Downloads

589

Version

0.4.6

License

GPL (>= 2)

Issues

5

Pull Requests

0

Stars

4

Forks

0

Maintainer

Sam Watson

Last Published

September 14th, 2023

Functions in glmmrBase (0.4.6)

glmmrBase-package

tools:::Rd_package_title("glmmrBase")
mcnr_family

Returns the file name and type for MCNR function
MeanFunction

R6 Class representing a mean function/linear predictor
Beta

Beta distribution declaration
Model

A GLMM Model
Covariance

R6 Class representing a covariance function and data
match_rows

Generate matrix mapping between data frames
nest_df

Generate nested block structure
cross_df

Generate crossed block structure
progress_bar

Generates a progress bar
cycles

Generates all the orderings of a
print.mcml

Prints an mcml fit output
setParallel

Disable or enable parallelised computing
ytest1

Data for model tests
nelder

Generates a block experimental structure using Nelder's formula
summary.mcml

Summarises an mcml fit output
yexample312a

Data for first example in Section 3.12 of JSS paper
yexample312b

Data for second example in Section 3.12 of JSS paper
yexample312c

Data for third example in Section 3.12 of JSS paper