fbabd2aaa7394410VgnVCM100000c2b1d38dRCRDapproved/UMICH/stats/Home/News & Events/Statistics SeminarDepartment Seminar Series: Michael Perlman, Extinction or Explosion in a Galton-Watson Branching Process: Testing or Prediction?###@###(Tue, 22 Apr 2014)Department Seminar Series: Michael Perlman, Extinction or Explosion in a Galton-Watson Branching Process: Testing or Prediction?###@###(Tue, 22 Apr 2014)4th Floor Forum, Palmer Commonsstats139819500000013981950000003:30 PM<p style=" line-height: 115%; font-size: 11.0pt; margin-top: 0in; margin-right: 0in; font-family: Calibri,sans-serif; margin-bottom: 10.0pt; margin-left: 0in;"><span style=" font-size: medium; color: #222222; background: white; font-family: 'Times New Roman';">Abstract: &nbsp;Testing subcriticality vs. supercriticality in a Galton-Watson branching process is a classical problem in statistical inference for stochastic processes. However, a decision-theoretic analysis shows&nbsp;that this problem is more complex than the literature suggests and that the basis of a standard test procedure is somewhat dubious. Fortunately, this classical testing problem usually is not the one of actual interest. Of more interest is the problem of predicting whether the&nbsp;<i>current&nbsp;</i>realization of the branching process will terminate (become extinct) or explode.&nbsp; This second problem, which does not seem to have been addressed before, also can be formulated as a hypothesis-testing problem for which a relatively simple solution is available, based on the classical Wald sequential probability ratio test. An application is given to the outbreak of pertussis (whooping cough) in Washington State in 2012.&nbsp;</span></p> <p style=" line-height: 115%; font-size: 11.0pt; background: white; margin-top: 0in; margin-right: 0in; font-family: Calibri,sans-serif; margin-bottom: 10.0pt; margin-left: 0in;"><span style=" font-size: medium; color: #222222; font-family: 'Times New Roman';">(This is joint work with Peter Guttorp).</span></p>Nlorieannbzuniga1396894563837cbabd2aaa7394410VgnVCM100000c2b1d38d____once11112newnewMichael Perlman, Ph.D., Professor, Department of Statistics, University of Washingtonhttp://www.stat.washington.edu/personnel/people.php?id=75