On the flexibility of the design of Multiple Try Metropolis schemes

Abstract

The Multiple Try Metropolis (MTM) method is a generalization of the classical Metropolis-Hastings algorithm in which the next state of the chain is chosen among a set of samples, according to normalized weights. In the literature, several extensions have been proposed. In this work, we show and remark upon the flexibility of the design of MTM-type methods, fulfilling the detailed balance condition. We discuss several possibilities and show different numerical results.

References in corpus (2)

• Interacting Multiple Try Algorithms with Different Proposal Distributions
• A multi-point Metropolis scheme with generic weight functions

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