tglm: Binary Regressions under Independent Student-t Priors

Use Gibbs sampler with Polya-Gamma data augmentation to fit logistic and probit regression under independent Student-t priors (including Cauchy priors and normal priors as special cases).

Version: 1.0
Depends: R (≥ 2.14.0)
Imports: BayesLogit, mvtnorm, coda, truncnorm
Published: 2015-07-26
Author: Yingbo Li
Maintainer: Yingbo Li <ybli at clemson.edu>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: no
CRAN checks: tglm results

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Reference manual: tglm.pdf
Package source: tglm_1.0.tar.gz
Windows binaries: r-devel: tglm_1.0.zip, r-release: tglm_1.0.zip, r-oldrel: tglm_1.0.zip
OS X El Capitan binaries: r-release: tglm_1.0.tgz
OS X Mavericks binaries: r-oldrel: tglm_1.0.tgz

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