Description: Belief propagation methods in Bayesian Networks to propagate evidence through the network. The implementation of these methods are based on the article: Cowell, RG (2005). Local Propagation in Conditional Gaussian Bayesian Networks <https://www.jmlr.org/papers/v6/cowell05a.html>. For details please see Yu et. al. (2020) BayesNetBP: An R Package for Probabilistic Reasoning in Bayesian Networks <doi:10.18637/jss.v094.i03>. The optional 'cyjShiny' package for running the Shiny app is available at <https://github.com/cytoscape/cyjShiny>. Please see the example in the documentation of 'runBayesNetApp' function for installing 'cyjShiny' package from GitHub.

Description: This package provides efficient Bayesian nonparametric models for network discovery
Author: Zhou Lan, Jian Kang, Tianwei Yu, Yize Zhao

Title: Bayesian Group Sequential Design for Ordinal Data
Authors@R: c(person("Chengxue", "Zhong", role = c("aut", "cre"),
Description: The proposed group-sequential trial design is based on Bayesian methods for ordinal endpoints,
including three methods, the proportional-odds-model (PO)-based, non-proportional-odds-model (NPO)-based,
and PO/NPO switch-model-based designs, which makes our proposed methods generic to be able to deal with
Thomas A. Murray, Ying Yuan, Peter F. Thall, Joan H. Elizondo, Wayne L.Hofstetter (2018) <doi:10.1111/biom.12842>.
Chengxue Zhong, Haitao Pan, Hongyu Miao (2021) <arXiv:2108.06568>.
Imports: ordinal, schoolmath, tidyverse, fda, coda, gsDesign,
superdiag, ggplot2, madness, rjmcmc, R2jags, rjags, methods

superdiag, ggplot2, madness, rjmcmc, R2jags, rjags, methods,

Imports: ordinal, schoolmath, coda, gsDesign, superdiag, ggplot2,
madness, rjmcmc, R2jags, rjags, methods,

Description: Bayesian power/type I error calculation and model fitting using
the power prior and the normalized power prior for generalized linear models.
The Bayesian clinical trial design methodology is described in Chen et al. (2011)
<doi:10.1093/biostatistics/kxy009>. The normalized power prior is described in Duan et al. (2006)