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jun 2004 Stability of the tail Markov chain and the evaluation of improper priors for an exponential rate parameter
James P. Hobert, Dobrin Marchev, Jason Schweinsberg
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Bernoulli 10(3): 549-564 (jun 2004). DOI: 10.3150/bj/1089206409

Abstract

Let Z be a continuous random variable with a lower semicontinuous density f that is positive on (0,∞) and 0 elsewhere. Put G(x) = ∨x f(z)dz. We study the tail Markov chain generated by Z, defined as the Markov chain Ψ=(Ψn)n=0 with state space [0, ∞) and Markov transition density k(y|x) = f(y+x)/G(x). This chain is irreducible, aperiodic and reversible with respect to G. It follows that Ψ is positive recurrent if and only if Z has a finite expectation. We prove (under regularity conditions) that if E Z = ∞, then Ψ is null recurrent if and only if 1 1/[ z3 f(z) ] dz = ∞. Furthermore, we describe an interesting decision-theoretic application of this result. Specifically, suppose that X is an Exp(θ) random variable; that is, X has density θe- θx for x>0. Let ν be an improper prior density for θ that is positive on (0,∞). Assume that 0 θ ν(θ) dθ< ∞, which implies that the posterior density induced by ν is proper. Let mν denote the marginal density of X induced by ν; that is, mν(x) = ∨0 θe-θx ν(θ) dθ. We use our results, together with those of Eaton and of Hobert and Robert, to prove that ν is a \cal P-admissible prior if 1 1/ [x2 mν(x)]dx = ∞.

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James P. Hobert. Dobrin Marchev. Jason Schweinsberg. "Stability of the tail Markov chain and the evaluation of improper priors for an exponential rate parameter." Bernoulli 10 (3) 549 - 564, jun 2004. https://doi.org/10.3150/bj/1089206409

Information

Published: jun 2004
First available in Project Euclid: 7 July 2004

zbMATH: 1049.60068
MathSciNet: MR2061443
Digital Object Identifier: 10.3150/bj/1089206409

Keywords: Admissibility , coupling , hazard rate , null recurrence , reversibility , Stochastic comparison , stochastically monotone Markov chain , transience

Rights: Copyright © 2004 Bernoulli Society for Mathematical Statistics and Probability

Vol.10 • No. 3 • jun 2004
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