Martino, LucaPascual del Olmo, VíctorRead, Jesse Michael2013-04-092013-04-092012-07Statistics & Probability Letters, Volume 82, Issue 7, July 2012, Pages 1445-1453.0167-7152http://hdl.handle.net/10016/16641The multi-point Metropolis algorithm is an advanced MCMC technique based on drawing several correlated samples at each step and choosing one of them according to some normalized weights. We propose a variation of this technique where the weight functions are not specified, i.e., the analytic form can be chosen arbitrarily. This has the advantage of greater flexibility in the design of high-performance MCMC samplers. We prove that our method fulfills the balance condition, and provide a numerical simulation. We also give new insight into the functionality of different MCMC algorithms, and the connections between them.application/pdfeng©ElsevierMultiple Try Metropolis algorithmMulti-point Metropolis algorithmMCMC methodsresearch articleInformática10.1016/j.spl.2012.04.008open access144571453Statistics and probability letters82AR/0000010121