Adaptive sampling for detecting a change point in the past
作者:
David Assaf,
Ya'acov Ritov,
期刊:
Sequential Analysis
(Taylor Available online 1992)
卷期:
Volume 11,
issue 3
页码: 237-255
ISSN:0747-4946
年代: 1992
DOI:10.1080/07474949208836257
出版商: Marcel Dekker, Inc.
关键词: dynamic sampling;stochastic approximation;Brow-nian motion
数据来源: Taylor
摘要:
Consider the problem of estimating a change point in the drift of Brownian motion which is known to have occurred at some time during the time interval [0,1], Rather than observing the process, we use "adaptive (dynamic) sampling" which allows us to continuously select the time points at which increments of the motion may be observed. Our main results are that the steepest descent method will continuosly select the current Bayes estimator of the change point as the next time point to observe. The method results in a very convergence rate.
点击下载:
PDF (461KB)
返 回