Paul Marjoram

Divison of Biostatistics, Dept. of Preventive Medicine,

University of Southern California

Hosted by Magnus Nordborg

Abstract:

Approximation Bayesian computation [ABC] is an analysis approach that has arisen in response to

the recent trend to collect data that is both much more complex, and of much higher dimension, than has historically

been the case. This has led to many existing analysis methods becoming intractable because of difficulties in calculating the

likelihood function. ABC circumvents this issue by replacing calculation of the likelihood with a

simulation step in which it is estimated in one way or another. In this talk I will give an overview of

the ABC approach and then give examples of applications of ABC, including mathematical population

genetics, the context in which it first arose, and agent-based models of behavior and tumor growth.