Monitoring a Bernoulli process subject to gradual changes in the success rates of a sequence of Bernoulli random variables

We look at a sequence of Bernoulli random variables where the success rates change from θ 1 to θ 2 . We will assume that both the success rates before and after the change are known. We also assume that this change does not happen abruptly but gradually over a period of time η where η is known. We c...

Full description

Saved in:
Bibliographic Details
Published inSequential analysis Vol. 41; no. 3; pp. 310 - 324
Main Author Brown, Marlo
Format Journal Article
LanguageEnglish
Published Philadelphia Taylor & Francis 30.09.2022
Taylor & Francis Ltd
Subjects
Bayesian stopping rules
change-point detection
dynamic programming
False alarms
gradual changes
Random variables
Online AccessGet full text

Cover

More Information
Summary:We look at a sequence of Bernoulli random variables where the success rates change from θ 1 to θ 2 . We will assume that both the success rates before and after the change are known. We also assume that this change does not happen abruptly but gradually over a period of time η where η is known. We calculate the probability that the change has started and completed. We also look at optimal stopping rules assuming that there is a cost for a false alarm and a cost per time unit to stop early.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:0747-4946
1532-4176
DOI:10.1080/07474946.2022.2092137