Sequential Change-Point Detection When the Pre- and Post-Change Parameters are Unknown

Abstract

We describe asymptotically optimal Bayesian and frequentist solutions to the problem of sequential change-point detection in multiparameter exponential families when the pre- and post-change parameters are unknown. In this connection we also address certain issues recently raised by Mei (2008 Mei , Y. ( 2008 ). Is Average Run Length to False Alarm Always an Information Criterion? Sequential Analysis 27 : 351 – 376 . [Google Scholar]) concerning performance criteria for detection rules in this setting.

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