Title
An adaptive backward coupling Metropolis algorithm for truncated distributions
Department/School
Mathematics
Date
10-11-2007
Document Type
Article
Keywords
Markov Chain Monte Carlo, independent Metropolis algorithm, location parameter, truncated normal distribution, backwards coupling
Abstract
In the paper, a new version of the independent Metropolis algorithm is considered, combining adaptive proposals with perfect sampling. construction of a non-regenerative adaptive Metropolis algorithm follows. A backwards coupling procedure is applied after each adaptation in order to guarantee the St.ationarity of the target. The result is a perfect sample from the target distribution with undesirable positive autocorrelations suppressed by adaptations. Performance of the suggested algorithm is examined using several examples of uniform and Gaussian proposals for truncated non-Gaussian targets. These examples are related to a problem of detection of the point source of a scattered signal.
Published in
Model Assisted Statistics and Applications
Citation/Other Information
Shemyakin, A. (2007). An adaptive backward coupling metropolis algorithm for truncated distributions. MASA. Model Assisted Statistics and Applications. 2. 10.3233/MAS-2007-2304.