Seminar | March 1 | 3:10-4 p.m. | 340 Evans Hall

 Adrian Gonzalez Casanova, National Autonomous University of Mexico and UC Berkeley

 Department of Statistics

Heuristically, two stochastic processes are dual if one can study one using the other. More formally, let (X_t) and (Y_t) be two real valued processes and let H be a measurable, R^2 \mapsto R function. We say that (X_t) and (Y_t) are H-dual if E[H(X_t,y)|X_0=x]=E[H(x,Y_t)|Y_0=y].

Sampling Duality is stochastic duality using a duality function S(n,x) of the form ¨what is the probability that all the members of a sample of size n are of certain type, given that the number (or frequency) of that type of individuals is x¨. Implicitly, this technique can be traced back to the work of Pascal. Explicitly, it was studied in a paper of Martin Möhle in 1999 in the context of population genetics. We will discuss several examples in which this technique is useful, including Haldane's formula for the fixation probability of a beneficial mutation and the long standing open question in theoretical evolution of the rate of the Muller Ratchet.

 lfzhang@berkeley.edu, 510-0000000

 Lingfu Zhang,  lfzhang@berkeley.edu,  510-000-0000

Event Date
-
Status
Happening As Scheduled
Primary Event Type
Seminar
Location
340 Evans Hall
Performers
Adrian Gonzalez Casanova, National Autonomous University of Mexico and UC Berkeley
Event ID
151511