Package: hbbr 1.1.2

Saurabh Mukhopadhyay

hbbr: Hierarchical Bayesian Benefit-Risk Assessment Using Discrete Choice Experiment

Implements assessment of benefit-risk balance using Bayesian Discrete Choice Experiment. For more details see the article by Mukhopadhyay et al. (2019) <doi:10.1080/19466315.2018.1527248>.

Authors:Saurabh Mukhopadhyay [aut], Saurabh Mukhopadhyay [cre]

hbbr_1.1.2.tar.gz
hbbr_1.1.2.tar.gz(r-4.7-any)hbbr_1.1.2.tar.gz(r-4.6-any)
hbbr_1.1.2.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
hbbr/json (API)

# Install 'hbbr' in R:
install.packages('hbbr', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))
Uses libs:
  • jags– Just Another Gibbs Sampler for Bayesian MCMC
  • c++– GNU Standard C++ Library v3
Datasets:
  • hbbrPilotResp - A list consisting of pilot data and associated discrete choice design information for the HBBR model framework.
  • simAugData - A list consisting of simulated data, design, baseline profiles, and true part-worth matrix for the Augmented HBBR model framework.

On CRAN:

Conda:

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

jagscpp

1.00 score 228 downloads 2 exports 15 dependencies

Last updated from:39f252c403. Checks:4 OK. Indexed: no.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK186
source / vignettesOK169
linux-release-x86_64OK187
wasm-releaseOK104

Exports:hbbr.FithbbrAug.Fit

Dependencies:abindbootclicodagluelatticelifecyclemagrittrR2jagsR2WinBUGSrjagsrlangstringistringrvctrs