ESS++: a C++ objected-oriented algorithm for Bayesian stochastic search model exploration
نویسندگان
چکیده
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.
منابع مشابه
Joint Bayesian Stochastic Inversion of Well Logs and Seismic Data for Volumetric Uncertainty Analysis
Here in, an application of a new seismic inversion algorithm in one of Iran’s oilfields is described. Stochastic (geostatistical) seismic inversion, as a complementary method to deterministic inversion, is perceived as contribution combination of geostatistics and seismic inversion algorithm. This method integrates information from different data sources with different scales, as prior informat...
متن کاملBayesian structural learning and estimation in Gaussian graphical models
We propose a new stochastic search algorithm for Gaussian graphical models called the mode oriented stochastic search. Our algorithm relies on the existence of a method to accurately and efficiently approximate the marginal likelihood associated with a graphical model when it cannot be computed in closed form. To this end, we develop a new Laplace approximation method to the normalizing constan...
متن کاملA Combined Stochastic Programming and Robust Optimization Approach for Location-Routing Problem and Solving it via Variable Neighborhood Search algorithm
The location-routing problem is one of the combined problems in the area of supply chain management that simultaneously make decisions related to location of depots and routing of the vehicles. In this paper, the single-depot capacitated location-routing problem under uncertainty is presented. The problem aims to find the optimal location of a single depot and the routing of vehicles to serve th...
متن کاملA stochastic network design of bulky waste recycling – a hybrid harmony search approach based on sample approximation
Facing supply uncertainty of bulky wastes, the capacitated multi-product stochastic network design model for bulky waste recycling is proposed in this paper. The objective of this model is to minimize the first-stage total fixed costs and the expected value of the second-stage variable costs. The possibility of operation costs and transportation costs for bulky waste recycling is considered ...
متن کاملApplications of the Mode Oriented Stochastic Search (MOSS) Algorithm for Discrete Multi-way Data to Genomewide Studies
We present a Bayesian variable selection procedure that is applicable to genomewide studies involving a combination of clinical, gene expression and genotype information. We use the Mode Oriented Stochastic Search (MOSS) algorithm of Dobra and Massam (2010) to explore regions of high posterior probability for regression models involving discrete covariates and to perform hierarchical log-linear...
متن کامل