This package contains functions to estimate the GLMM-AR(p) model for analyzing discrete time-series cross-sectional data via Markov Chain Monte Carlo simulation. The simulation is done only with the R language. The model returns draws of the parameter posteriors selected by the user in a list format. Each parameter chain is returned as a matrix. The user is responsible to summarize the mcmc output by using the coda package. GLMMarp also contains several useful utility functions, including an independent function for computing the Bayes factor with GLMM-AR(p) output, a function to recover the random coefficients at the individual level, and a function to do prediction by using the posterior distributions. The package also contains a library of supporting functions for the MCMC simulation and Bayes factor estimation. In this version, no tools for visualization are provided. To use the functions in this package, the user needs to load the following two packages by him/herself: code{panel} and code{bayesSurv}, because the two packages have no namespace.

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  1. GaƂecki, Andrzej; Burzykowski, Tomasz: Linear mixed-effects models using R. A step-by-step approach (2013)