Published by the Foundation for Open Access Statistics Editors-in-chief: Bettina Grün, Torsten Hothorn, Edzer Pebesma, Achim Zeileis    ISSN 1548-7660; CODEN JSSOBK
Authors: Karel Van den Meersche, Karline Soetaert, Dick Van Oevelen
Title: xsample(): An R Function for Sampling Linear Inverse Problems
Abstract: An R function is implemented that uses Markov chain Monte Carlo (MCMC) algorithms to uniformly sample the feasible region of constrained linear problems. Two existing hit-and-run sampling algorithms are implemented, together with a new algorithm where an MCMC step reflects on the inequality constraints. The new algorithm is more robust compared to the hit-and-run methods, at a small cost of increased calculation time.

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Paper: xsample(): An R Function for Sampling Linear Inverse Problems     Download PDF (Downloads: 4412)
Supplements:
limSolve_1.5.tar.gz: R source package Download (Downloads: 1624; 721KB)
v30c01.R: R example code from the paper Download (Downloads: 1324; 4KB)
DOI: 10.18637/jss.v030.c01

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Paper: Creative Commons Attribution 3.0 Unported License
Code: GNU General Public License (at least one of version 2 or version 3) or a GPL-compatible license.