Package: bhpm 1.8.1

bhpm: Bayesian Hierarchical Poisson Models for Multiple Grouped Outcomes with Clustering

Bayesian hierarchical methods for the detection of differences in rates of related outcomes for multiple treatments for clustered observations (Carragher et al. (2020) <doi:10.1002/sim.8563>). This software was developed for the Precision Drug Theraputics: Risk Prediction in Pharmacoepidemiology project as part of a Rutherford Fund Fellowship at Health Data Research (UK), Medical Research Council (UK) award reference MR/S003967/1 (<https://gtr.ukri.org/>). Principal Investigator: Raymond Carragher.

Authors:Raymond Carragher [aut, cre]

bhpm_1.8.1.tar.gz
bhpm_1.8.1.zip(r-4.7)bhpm_1.8.1.zip(r-4.6)bhpm_1.8.1.zip(r-4.5)
bhpm_1.8.1.tgz(r-4.6-x86_64)bhpm_1.8.1.tgz(r-4.6-arm64)bhpm_1.8.1.tgz(r-4.5-x86_64)bhpm_1.8.1.tgz(r-4.5-arm64)
bhpm_1.8.1.tar.gz(r-4.7-arm64)bhpm_1.8.1.tar.gz(r-4.7-x86_64)bhpm_1.8.1.tar.gz(r-4.6-arm64)bhpm_1.8.1.tar.gz(r-4.6-x86_64)
bhpm_1.8.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
bhpm/json (API)

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

Bug tracker:https://github.com/rcarragh/bhpm/issues

Uses libs:
  • c++– GNU Standard C++ Library v3
Datasets:

On CRAN:

Conda:

cpp

3.56 score 2 stars 18 scripts 278 downloads 18 exports 2 dependencies

Last updated from:7dee63cc76. Checks:11 NOTE, 2 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64NOTE144
linux-devel-x86_64NOTE139
source / vignettesOK197
linux-release-arm64NOTE139
linux-release-x86_64NOTE136
macos-release-arm64NOTE121
macos-release-x86_64NOTE275
macos-oldrel-arm64NOTE90
macos-oldrel-x86_64NOTE333
windows-develNOTE139
windows-releaseNOTE149
windows-oldrelNOTE142
wasm-releaseOK95

Exports:bhpm.cluster.1a.hier2bhpm.cluster.1a.hier3bhpm.cluster.BB.hier2bhpm.cluster.BB.hier3bhpm.convergence.diagbhpm.gen.initial.valuesbhpm.global.sim.param.defaultsbhpm.hyper.param.defaultsbhpm.monitor.defaultsbhpm.monitor.samplesbhpm.npmbhpm.pmbhpm.pointmass.weightsbhpm.print.convergence.summarybhpm.print.summary.statsbhpm.pthetabhpm.sim.control.paramsbhpm.summary.stats

Dependencies:codalattice

Readme and manuals

Help Manual

Help pageTopics
Bayesian Hierarchical Possion Models for Mulitple Grouped Outcomes with Clusteringbhpm-package
A Two-Level Hierarchical Model for Grouped Data with Clusters and without Point-Mass.bhpm.cluster.1a.hier2
A Three-Level Hierarchical Model for Grouped Data with Clusters and without Point-Mass.bhpm.cluster.1a.hier3
A Two-Level Hierarchical Model for grouped data and clusters with Point-Mass.bhpm.cluster.BB.hier2
A Three-Level Hierarchical Model for grouped data and clusters with Point-Mass.bhpm.cluster.BB.hier3
Cluster analysis data.bhpm.cluster.data1
Cluster analysis data.bhpm.cluster.data2
Convergence Diagnostics of the Simulationbhpm.convergence.diag
Generate a template simulation initial values.bhpm.gen.initial.values
Generate default global simulation parameters for a model.bhpm.global.sim.param.defaults
Generate default hyperparameter values for a model.bhpm.hyper.param.defaults
Generate default variable monitor list for a model.bhpm.monitor.defaults
Generate a template for choosing which samples to monitor.bhpm.monitor.samples
Cluster analysis data.bhpm.multi.treatments
Cluster analysis data.bhpm.multi.treatments.random.order
Fit a Bayesian Hierarchical Model for Grouped Data with Clusters and without Point-Mass.bhpm.npm
A Bayesian Hierarchical Model for grouped data and clusters with Point-Mass.bhpm.pm
Generate a template for the point-mass weightings.bhpm.pointmass.weights
Print a Summary of the Convergence Diagnostics of the Simulationbhpm.print.convergence.summary
Print the Summary Statistics of Posterior Distributionsbhpm.print.summary.stats
Reports the posterior probability that theta (the increase in the log-odds) is greater than zero, zero, and less than zero for each outcomebhpm.ptheta
Generate a template for the individual model parameter simulation control parameters.bhpm.sim.control.params
Summary Statistics for the Posterior Distributions in the model.bhpm.summary.stats
Cluster analysis data.demo.cluster.data