Geometric ergodicity of Metropolis algorithms.

Jarner, Søren Fiig and Hansen, Ernst (2000) Geometric ergodicity of Metropolis algorithms. Stochastic Processes and their Applications, 85 (2). pp. 341-361.

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Abstract

In this paper we derive conditions for geometric ergodicity of the random-walk-based Metropolis algorithm on . We show that at least exponentially light tails of the target density is a necessity. This extends the one-dimensional result of Mengersen and Tweedie (1996, Ann. Statist. 24, 101–121). For super-exponential target densities we characterize the geometrically ergodic algorithms and we derive a practical sufficient condition which is stable under addition and multiplication. This condition is especially satisfied for the class of densities considered in Roberts and Tweedie (1996, Biometrika 83, 95–110).

Item Type:
Journal Article
Journal or Publication Title:
Stochastic Processes and their Applications
Uncontrolled Keywords:
/dk/atira/pure/subjectarea/asjc/2600/2611
Subjects:
?? monte carlsmetropolis algorithmgeometric ergodicitysuper-exponential densitiesmodelling and simulationapplied mathematicsstatistics and probabilityqa mathematics ??
ID Code:
19354
Deposited By:
Deposited On:
17 Nov 2008 14:50
Refereed?:
Yes
Published?:
Published
Last Modified:
15 Jul 2024 09:42