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BiG (version 0.1.0)

Bayesian Aggregation in Genomic Applications

Description

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.

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Version

Install

install.packages('BiG')

Monthly Downloads

6

Version

0.1.0

License

GPL-3

Maintainer

Xue Li

Last Published

October 16th, 2017

Functions in BiG (0.1.0)

BiG_DA

BiG with half-t prior through a data augmentation approach
BiG_diffuse

BiG with diffuse Inverse Gamma/Uniform prior
init_W

Generate initial values for W
qtruncgamma

Truncated Gamma distribution
sim_lvm

Simulate rank data from latent variable model