ESS++: a C++ objected-oriented algorithm for Bayesian stochastic search model exploration |
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Authors: | Bottolo Leonardo Chadeau-Hyam Marc Hastie David I Langley Sarah R Petretto Enrico Tiret Laurence Tregouet David Richardson Sylvia |
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Affiliation: | Department of Epidemiology and Biostatistics, Imperial College London, UK. l.bottolo@imperial.ac.uk |
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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. AVAILABILITY: C++ source code and documentation including compilation instructions are available under GNU licence at http://bgx.org.uk/software/ESS.html. |
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