The Annals of Statistics

Dynamic Sampling Procedures for Detecting a Change in the Drift of Brownian Motion: A Non-Bayesian Model

David Assaf and Ya'acov Ritov

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Abstract

We consider dynamic procedures for sampling from a process (a Brownian motion) and stopping it after a change is detected. The basic idea is to conduct a sequence of similar SPRT's, each one of them done in negligible time, while not sampling at all between them. The procedures detect the change point much faster than the standard procedures with the same sampling rate and time to false alarm, but hold the sampling rate constant.

Article information

Source
Ann. Statist., Volume 17, Number 2 (1989), 793-800.

Dates
First available in Project Euclid: 12 April 2007

Permanent link to this document
https://projecteuclid.org/euclid.aos/1176347143

Digital Object Identifier
doi:10.1214/aos/1176347143

Mathematical Reviews number (MathSciNet)
MR994268

Zentralblatt MATH identifier
0672.62083

JSTOR
links.jstor.org

Subjects
Primary: 62L10: Sequential analysis
Secondary: 62L20: Stochastic approximation

Keywords
CUSUM procedure Roberts-Shiryayev procedure SPRT Brownian motion dynamic sampling

Citation

Assaf, David; Ritov, Ya'acov. Dynamic Sampling Procedures for Detecting a Change in the Drift of Brownian Motion: A Non-Bayesian Model. Ann. Statist. 17 (1989), no. 2, 793--800. doi:10.1214/aos/1176347143. https://projecteuclid.org/euclid.aos/1176347143


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