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On the problems of sequential statistical inference for Wiener processes with delayed observations

Gapeev, Pavel V. (2020) On the problems of sequential statistical inference for Wiener processes with delayed observations. Statistical Papers, 61 (4). pp. 1529-1544. ISSN 0932-5026

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Identification Number: 10.1007/s00362-020-01178-0

Abstract

We study the sequential hypothesis testing and quickest change-point (or disorder) detection problems with linear delay penalty costs for observable Wiener processes under (constantly) delayed detection times. The method of proof consists of the reduction of the associated delayed optimal stopping problems for one-dimensional diffusion processes to the equivalent free-boundary problems and solution of the latter problems by means of the smooth-fit conditions. We derive closed-form expressions for the Bayesian risk functions and optimal stopping boundaries for the associated weighted likelihood ratio processes in the original problems of sequential analysis.

Item Type: Article
Official URL: https://www.springer.com/journal/362
Additional Information: © 2020 The Authors
Divisions: Mathematics
Subjects: Q Science > QA Mathematics
H Social Sciences > HA Statistics
Date Deposited: 16 Apr 2020 14:12
Last Modified: 20 Oct 2020 06:02
URI: http://eprints.lse.ac.uk/id/eprint/104072

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