ESS++: a C++ objected-oriented algorithm for Bayesian stochastic search model exploration

Bioinformatics. 2011 Feb 15;27(4):587-8. doi: 10.1093/bioinformatics/btq684. Epub 2011 Jan 13.


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

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Algorithms*
  • Bayes Theorem*
  • Gene Expression Regulation
  • Linear Models
  • Models, Statistical*
  • Programming Languages*
  • Software*
  • Stochastic Processes