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# CITATION file created with {cffr} R package
# See also: https://docs.ropensci.org/cffr/
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cff-version: 1.2.0
message: 'To cite package "GHS" in publications use:'
type: software
license: GPL-2.0-only
title: 'GHS: Graphical Horseshoe MCMC Sampler Using Data Augmented Block Gibbs Sampler'
version: '0.1'
abstract: Draw posterior samples to estimate the precision matrix for multivariate
  Gaussian data. Posterior means of the samples is the graphical horseshoe estimate
  by Li, Bhadra and Craig(2017) <arXiv:1707.06661>. The function uses matrix decomposition
  and variable change from the Bayesian graphical lasso by Wang(2012) <https://doi.org/10.1214/12-BA729>,
  and the variable augmentation for sampling under the horseshoe prior by Makalic
  and Schmidt(2016) <arXiv:1508.03884>. Structure of the graphical horseshoe function
  was inspired by the Bayesian graphical lasso function using blocked sampling, authored
  by Wang(2012) <https://doi.org/10.1214/12-BA729>.
authors:
- family-names: Srivastava
  given-names: Ashutosh
  email: srivas48@purdue.edu
- family-names: Bhadra
  given-names: Anindya
  email: bhadra@purdue.edu
repository: https://CRAN.R-project.org/package=GHS
date-released: '2018-10-30'
contact:
- family-names: Srivastava
  given-names: Ashutosh
  email: srivas48@purdue.edu