Bottolo, Leonardo, Chadeau-Hyam, Marc, Hastie, David I., Langley, Sarah R. ![]() |
Official URL: https://doi.org/10.1093/bioinformatics/btq684
Abstract
Summary: ESS++ is a C++ implementation of a fully Bayesian variable selection approach for single and multiple response linear regression. ESS++ works well both when the number of observations is larger than the number of predictors and in the ‘large p, small n’ case. In the current version, ESS++ can handle several hundred observations, thousands of predictors and a few responses simultaneously. The core engine of ESS++ for the selection of relevant predictors is based on Evolutionary Monte Carlo. Our implementation is open source, allowing community-based alterations and improvements.
Item Type: | Article |
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Date Type: | Publication |
Status: | Published |
Schools: | Biosciences |
Publisher: | Oxford University Press |
ISSN: | 1367-4803 |
Date of Acceptance: | 7 December 2010 |
Last Modified: | 05 Sep 2023 13:30 |
URI: | https://orca.cardiff.ac.uk/id/eprint/162141 |
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