OPTIMAL SEQUENTIAL TESTS FOR MONITORING CHANGES IN THE DISTRIBUTION OF FINITE OBSERVATION SEQUENCES

This study proposes a method for constructing an optimal sequential test that monitors changes in the distribution of finite observation sequences with a general dependence structure. This method allows us to prove that different optimal sequential tests can be constructed for different performance measures of detection delay times. A formula is presented to calculate the value of the generalized out-of-control average run length for every optimal sequential test. Moreover, we show that there is an equivalent optimal control limit that does not depend on the test statistic directly when the post-change conditional densities (probabilities) of the observation sequences do not depend on the change time. The detection performance of six sequential tests, including two optimal sequential tests, are illustrated using numerical simulations and a real-data example.