BiG: Bayesian Aggregation in Genomic Applications

An implementation of Bayesian Aggregation in Genomic Applications (BiG), where BiG is a Bayesian latent variable approach to aggregation of partial and top ranked lists (Li et. al in preparation). It provides implementations for three different prior setups for variance/standard deviation parameters: diffuse inverse gamma (IG), diffuse uniform, half-t.

Version: 0.1.0
Depends: R (≥ 2.15.0)
Imports: truncnorm
Published: 2017-10-16
Author: Xue Li
Maintainer: Xue Li <xuel at smu.edu>
License: GPL-3
NeedsCompilation: no
CRAN checks: BiG results

Downloads:

Reference manual: BiG.pdf
Package source: BiG_0.1.0.tar.gz
Windows binaries: r-devel: BiG_0.1.0.zip, r-release: BiG_0.1.0.zip, r-oldrel: BiG_0.1.0.zip
OS X El Capitan binaries: r-release: BiG_0.1.0.tgz
OS X Mavericks binaries: r-oldrel: BiG_0.1.0.tgz

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