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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) <doi: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) <doi:10.1214/12-BA729>.

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conda 1.0 MB | noarch/r-ghs-0.1-r43h142f84f_0.tar.bz2  1 year and 2 months ago 24 main
conda 1.0 MB | noarch/r-ghs-0.1-r42h142f84f_0.tar.bz2  2 years and 9 months ago 53 main
conda 1.0 MB | noarch/r-ghs-0.1-r36h6115d3f_0.tar.bz2  5 years and 22 days ago 123 main

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