Adaptive Sticky Generalized Metropolis

65 Pages Posted: 5 Sep 2013

See all articles by Luca Martino

Luca Martino

Complutense University of Madrid - Industrial and Financial Analysis Institute (IAIF)

Roberto Casarin

University Ca' Foscari of Venice - Department of Economics

Fabrizio Leisen

University of Kent - Canterbury Campus

David Luengo

Complutense University of Madrid - Industrial and Financial Analysis Institute (IAIF)

Date Written: August 20, 2013

Abstract

We introduce a new class of adaptive Metropolis algorithms called adaptive sticky algorithms for efficient general-purpose simulation from a target probability distribution. The transition of the Metropolis chain is based on a multiple-try scheme and the different proposals are generated by adaptive nonparametric distributions. Our adaptation strategy uses the interpolation of support points from the past history of the chain as in the adaptive rejection Metropolis. The algorithm efficiency is strengthened by a step that controls the evolution of the set of support points. This extra stage improves the computational cost and accelerates the convergence of the proposal distribution to the target. Despite the algorithms are presented for univariate target distributions, we show that they can be easily extended to the multivariate context by a Gibbs sampling strategy. We show the ergodicity of the proposed algorithms and illustrate their efficiency and effectiveness through some simulated examples involving target distributions with complex structures.

Keywords: Adaptive Markov chain Monte Carlo, Adaptive rejection Metropolis, Muliple-try Metropolis, Metropolis within Gibbs

JEL Classification: C1, C15, C11, C40, C63

Suggested Citation

Martino, Luca and Casarin, Roberto and Leisen, Fabrizio and Luengo, David, Adaptive Sticky Generalized Metropolis (August 20, 2013). University Ca' Foscari of Venice, Dept. of Economics Research Paper Series No. 19/WP/2013, Available at SSRN: https://ssrn.com/abstract=2320496 or http://dx.doi.org/10.2139/ssrn.2320496

Luca Martino

Complutense University of Madrid - Industrial and Financial Analysis Institute (IAIF) ( email )

Av Séneca
Madrid, 28040
Spain

Roberto Casarin (Contact Author)

University Ca' Foscari of Venice - Department of Economics ( email )

San Giobbe 873/b
Venice, 30121
Italy
+39 030.298.91.49 (Phone)
+39 030.298.88.37 (Fax)

HOME PAGE: http://sites.google.com/view/robertocasarin

Fabrizio Leisen

University of Kent - Canterbury Campus ( email )

Cornwallis Building
Canterbury, Kent CT2 7NF
United Kingdom

David Luengo

Complutense University of Madrid - Industrial and Financial Analysis Institute (IAIF) ( email )

Av Séneca
Madrid, 28040
Spain

Do you have a job opening that you would like to promote on SSRN?

Paper statistics

Downloads
31
Abstract Views
1,021
PlumX Metrics