Department of Mathematics & Statistics Calendar Week of February 19 - 25, 2007 Monday, February 19, 2007 President's Day Open House 12:30 PM Statistics Education Seminar 459 MSc Gary NONNEMACHER 3:30 PM Refreshments served prior to candidate research talk 459 MSc 3:45 PM ALGEBRA Candidate Research Talk 459 MSc Tuesday, February 20, 2007 Wednesday, February 21, 2007 10:30 AM Statistics Seminar 459 MSc Professor M. S. SRIVASTAVA, Visiting Lukacs Professor "Multivariate Theory for High Dimensional Data with Fewer Observations" TOPIC: False discovery rate and other procedures in large-scale multiple hypothesis testing -- CONTINUED 2:30 PM Frame Theory Seminar 400 MSc 3:30 PM Education Seminar 224 MSc Gary NONNEMACHER "Grading Fairly" 3:30 PM Refreshments served prior to candidate research talk 459 MSc 3:45 PM ALGEBRA Candidate Research Talk 459 MSc Thursday, February 22, 2007 10:45 - 11:20 AM Foundational Mathematics Committee 400 MSc 1:00 PM Personnel Committee Meeting 400 MSc Friday, February 23, 2007 11:30 AM Analysis Seminar 459 MSc Professor Kit C. CHAN "Common hypercyclic vectors for a path of hypercyclic operators, Part IV" 12:00 Noon Calendar Information Due to Cyndi for next week's calendar 1:30 PM - 3:20 PM Algebra Seminar 400 MSc 3:30 PM Refreshments served prior to the colloquium 459 MSc 3:45 PM Colloquium 459 MSC Dr. E. BAYRAKTAR, University of Michigan "Quickest Detection for a Poisson Process with a Phase-type Change-time Distribution" ABSTRACT: We consider a change detection problem in which the arrival rate of a Poisson process changes suddenly at some unknown and unobservable disorder time. It is assumed that the prior distribution of the disorder is known. The ob jective is to determine the disorder time with an online detection rule (a stopping time) in a way that balances the frequency of false alarm and detection delay in an optimal way. So far in the study of this problem, the prior distribution of the disorder time is taken to be exponential distribution for analytical tractability. Here, we will take the prior distribution to be a phase-type distribution, which is the distribution of the absorption time of a continuous time Markov chain with a discrete state space. We find the optimal stopping rule for this general case and give a numerical method that outputs epsilon-optimal strategies for any epsilon> 0. We illustrate our findings on several examples. Saturday, February 24, 2007 Sunday, February 25, 2007
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