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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

408

Version

0.4.6

License

GPL (>= 2)

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Repository

https://github.com/samuel-watson/glmmrBase

Maintainer

Sam Watson

Last Published

September 14th, 2023

Functions in glmmrBase (0.4.6)

glmmrBase-package

tools:::Rd_package_title("glmmrBase")

Returns the file name and type for MCNR function

R6 Class representing a mean function/linear predictor

Beta distribution declaration

R6 Class representing a covariance function and data

Generate matrix mapping between data frames

Generate nested block structure

Generate crossed block structure

Generates a progress bar

Generates all the orderings of a

Prints an mcml fit output

Disable or enable parallelised computing

Data for model tests

Generates a block experimental structure using Nelder's formula

Summarises an mcml fit output

Data for first example in Section 3.12 of JSS paper

Data for second example in Section 3.12 of JSS paper

Data for third example in Section 3.12 of JSS paper