The Annals of Mathematical Statistics

Optimum Decision Procedures for a Poisson Process Parameter

J. A. Lechner

Full-text: Open access

Abstract

This paper derives and exhibits the optimum Bayes solution to the following problem: Given a continuous-time Poisson process with unknown mean occurrence rate $\lambda$; to decide whether $\lambda > k$ or $\lambda < k$. The prior distribution is taken to be of Gamma type, with positive mean and finite variance. The cost of observation is taken proportional to the length of time the process is observed, and the cost of a wrong decision proportional to $|\lambda - k|$. The decision rule derived is optimum (in the sense of minimum expected cost) among all non-randomized sequential rules. Some of the results hold true, of course, for other cost functions and/or prior distributions. A method for treating the same problem with the inclusion of a constant setup cost is also given.

Article information

Source
Ann. Math. Statist., Volume 33, Number 4 (1962), 1384-1402.

Dates
First available in Project Euclid: 27 April 2007

Permanent link to this document
https://projecteuclid.org/euclid.aoms/1177704371

Digital Object Identifier
doi:10.1214/aoms/1177704371

Mathematical Reviews number (MathSciNet)
MR141205

Zentralblatt MATH identifier
0114.34401

JSTOR
links.jstor.org

Citation

Lechner, J. A. Optimum Decision Procedures for a Poisson Process Parameter. Ann. Math. Statist. 33 (1962), no. 4, 1384--1402. doi:10.1214/aoms/1177704371. https://projecteuclid.org/euclid.aoms/1177704371


Export citation