Bayes sequential estimation for a Poisson process under a LINEX loss function

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Title:	Bayes sequential estimation for a Poisson process under a LINEX loss function
Authors:	Hwang, L.-C.;Lee, C.-H.
Contributors:	Department of Statistics, Tunghai University
Keywords:	asymptotically non-deficient;asymptotically optimal;asymptotically pointwise optimal;Bayes sequential estimation;homogeneous Poisson process;LINEX loss function
Date:	2013
Issue Date:	2014-05-30T03:01:23Z (UTC)
Abstract:	In this paper, within the framework of a Bayesian model, we consider the problem of sequentially estimating the intensity parameter of a homogeneous Poisson process with a linear exponential (LINEX) loss function and a fixed cost per unit time. An asymptotically pointwise optimal (APO) rule is proposed. It is shown to be asymptotically optimal for the arbitrary priors and asymptotically non-deficient for the conjugate priors in a similar sense of Bickel and Yahav [Asymptotically pointwise optimal procedures in sequential analysis, in Proceedings of the Fifth Berkeley Symposium on Mathematical Statistics and Probability, Vol. 1, University of California Press, Berkeley, CA, 1967, pp. 401-413; Asymptotically optimal Bayes and minimax procedures in sequential estimation, Ann. Math. Statist. 39 (1968), pp. 442-456] and Woodroofe [A.P.O. rules are asymptotically non-deficient for estimation with squared error loss, Z. Wahrsch. verw. Gebiete 58 (1981), pp. 331-341], respectively. The proposed APO rule is illustrated using a real data set. ? 2013 Copyright Taylor and Francis Group, LLC.
Relation:	Statistics,Vol.47,Issue4,P.672-687
Appears in Collections:	[Department of Statistics ] Periodical Articles

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