Bayesian Aggregation in Genomic Applications
Overview
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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Documentation
- Help pages
- 5
- Examples that run
- 100%4 run in a plain check
- Exported functions with examples
- 80%
- Documented parameters
- 73%
- Return-value docs
- 0%
- Help pages citing references
- 0%
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Dependencies
Code & Tests
People & History
- RR 3.6.0 released · 2019-04-26
- archivedRemoved from CRAN2019-04-22check errors were not corrected despite reminders
- RR 3.5.0 released · 2018-04-23
- 0.1.02017-10-16
- RR 3.4.0 released · 2017-04-21
Package metadata
- First published
- 2017-10-16
- Total releases
- 1 / 9 yrs
- License
- GPL-3 OSI
- Minimum R
- ≥ 2.15.0
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