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Statistics Seminar
Department of Mathematical Sciences

DATE:Thursday, March 12, 2015
TIME:1:15pm to 2:15pm
SPEAKER:Heng Yang (Graduate Center, City University of New York)
TITLE:Simultaneous detection and identification with post-change uncertainty


We consider the problem of quickest detection of an abrupt change when there is uncertainty about the post-change distribution. Because of the uncertainty, We would like not only detecting the change point but also identifying the post-change distribution simultaneously. In particular we examine this problem in the continuous-time Wiener model where the drift of observations changes from zero to a drift randomly chosen from a collection. We set up the problem as a stochastic optimization in which the objective is to minimize a measure of detection delay subject to a frequency of false alarm constraint, while also identifying the value of the post-change drift up to pre-specified error bounds. We consider a composite rule involving the CUSUM reaction period, that is coupled with an identification function, and show that by choosing parameters appropriately, such a pair of composite rule and identification function can be asymptotically optimal of first order to detect the change point and simultaneously satisfies the error bounds to identify the post-change drift as the average first false alarm increases without bound. We also discuss the detection problem under different situations.

seminars/stat/03122015.txt · Last modified: 2015/02/07 17:49 by aleksey