cae1aeee88873410VgnVCM100000c2b1d38dRCRDapproved/UMICH/stats/Home/News & Events/Statistics SeminarDepartment Seminar Series: Vinayak Rao, Stochastic Processes for Point Pattern Data ###@###(Tue, 21 Jan 2014)Department Seminar Series: Vinayak Rao, Stochastic Processes for Point Pattern Data ###@###(Tue, 21 Jan 2014)1640 Chemistry<br>Reception at 3:30 pm in the Statistics Lounge, 450 WHstats139033800000013903380000004:00 PM<p style=" margin-bottom: 0pt; line-height: 114%; text-align: left; text-indent: 0pt; color: black; font-size: 10.0pt; margin-right: 0pt; font-family: 'Times New Roman'; margin-top: 0pt;"><span style=" font-size: 16.0pt; line-height: 114%;">Abstract: &nbsp;Point pattern data are ubiquitous in the natural and social sciences, with applications in fields like neuroscience, ecology, genetics, social networks and economics. The simplest model of such data is the Poisson process, with more complicated extensions including renewal processes, Matern repulsive processes and Hawkes processes. The Poisson process also underlies function and measure-valued stochastic processes like Markov jump processes (used in stochastic chemical kinetics, for instance), and completely random measures or Levy processes (used in Bayesian nonparametrics). In this talk, I will show how the latter connection&nbsp;allows the development of flexible models as well as efficient (and exact) Markov chain Monte Carlo algorithms. The resulting models and&nbsp;algorithms have wide applicability; I will consider problems from neuroscience, genetics and biometrics.</span></p> <p style=" margin-bottom: 0pt; text-align: left; text-indent: 0pt; color: black; font-size: 10.0pt; margin-right: 0pt; font-family: 'Times New Roman'; margin-top: 0pt;">&nbsp;</p>Nlorieannbzuniga13899749602179ae1aeee88873410VgnVCM100000c2b1d38d____once11112newnewVinayak Rao, Postdoctoral Associate, Department of Statistics, Duke Universityhttp://www.stat.duke.edu/~var11/