Detailed examples of applying the package are available at <arXiv:2112.14616>.

Suggests: rmarkdown, knitr, testthat (>= 3.0.0), ggplot2, kableExtra

Title: Bayesian Methods for Panel Data Modeling and Inference
Author: Chunhua Wu <chunhuawu@wustl.edu>, Siddhartha Chib
Depends: R (>= 2.5.0), MASS, coda, Formula
SystemRequirements: Gnu Scientific Library version >= 1.12
Description: This package contains functions for panel data modeling
and inference using Bayesian methods. It is a realization of
models described in Chib(2008): Panel Data Modeling and
Inference: A Bayesian Primer. Most functions utilized the GNU

Title: Bayesian Penalized Credible Regions
Author: Ander Wilson, Howard D. Bondell, and Brian J. Reich
Description: Fits the Bayesian penalized credible region variable and confounder selection methods.

Title: Variable Selection in a Hierarchical Bayesian Model for a Hazard
Authors@R: person("Andrew", "Chapple", email = "AndrewChapple21@gmail.com", role = c("aut", "cre"))
Description: Fits a piecewise exponential hazard to survival data using a
Hierarchical Bayesian model with an Intrinsic Conditional Autoregressive
formulation for the spatial dependency in the hazard rates for each piece.
This function uses Metropolis- Hastings-Green MCMC to allow the number of split
points to vary and also uses Stochastic Search Variable Selection to determine
what covariates drive the risk of the event. This function outputs trace plots
depicting the number of split points in the hazard and the number of variables
included in the hazard. The function saves all posterior quantities to the

Package: BayesPiecewiseICAR
Type: Package
Title: Hierarchical Bayesian Model for a Hazard Function
Version: 0.1.0
Author: person("Andrew", "Chapple", email = "Andrew.G.Chapple@rice.edu", role = c("aut", "cre"))
Maintainer: Andrew Chapple <Andrew.G.Chapple@rice.edu>
Description: Fits a piecewise exponential hazard to survival data using a
Hierarchical Bayesian model with an Intrinsic Conditional Autoregressive
formulation for the spatial dependency in the hazard rates for each piece.
This function uses Metropolis- Hastings-Green MCMC to allow the number of split
points to vary. This function outputs graphics that display the histogram of
the number of split points and the trace plots of the hierarchical parameters.
The function outputs a list that contains the posterior samples for the number
of split points, the location of the split points, and the log hazard rates
corresponding to these splits. Additionally, this outputs the posterior samples
of the two hierarchical parameters, Mu and Sigma^2.
License: GPL-2
LazyData: TRUE
RoxygenNote: 5.0.1
Depends: mvtnorm
NeedsCompilation: no
Packaged: 2016-07-27 15:16:18 UTC; Andrew
Repository: CRAN
Date/Publication: 2016-07-27 19:00:54