Package: BayesPieceHazSelect 1.1.0

BayesPieceHazSelect: Variable Selection in a Hierarchical Bayesian Model for a Hazard Function

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 desired path.

Authors:Andrew Chapple [aut, cre]

BayesPieceHazSelect_1.1.0.tar.gz
BayesPieceHazSelect_1.1.0.zip(r-4.7)BayesPieceHazSelect_1.1.0.zip(r-4.6)BayesPieceHazSelect_1.1.0.zip(r-4.5)
BayesPieceHazSelect_1.1.0.tgz(r-4.6-any)BayesPieceHazSelect_1.1.0.tgz(r-4.5-any)
BayesPieceHazSelect_1.1.0.tar.gz(r-4.7-any)BayesPieceHazSelect_1.1.0.tar.gz(r-4.6-any)
BayesPieceHazSelect_1.1.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html
card.svg |card.png
BayesPieceHazSelect/json (API)

# Install 'BayesPieceHazSelect' in R:
install.packages('BayesPieceHazSelect', repos = c('https://andrewgchapple.r-universe.dev', 'https://cloud.r-project.org'))

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

1.00 score 2 scripts 177 downloads 1 exports 1 dependencies

Last updated from:40d66bc0d5. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK111
source / vignettesOK158
linux-release-x86_64OK91
macos-release-arm64OK125
macos-oldrel-arm64OK145
windows-develOK73
windows-releaseOK72
windows-oldrelOK74
wasm-releaseOK87

Exports:PiecewiseBayesSelect

Dependencies:mvtnorm

Readme and manuals

Help Manual

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