EVENT DETAILS AND ABSTRACT

Title: Dirichlet approximation of genetic drift models
Speaker: Han Liang Gan
Speaker Info: Northwestern University
Brief Description:
Special Note:
Abstract:

A genetic drift model studies how gene variants and their frequencies evolve in time. However, even for a relatively innocuous looking model, exact distributions are often intractable. As a result, approximate distributions may be useful. The Dirichlet distribution takes values in K dimensional space where the sum of the entries is equal to 1. This makes it a natural candidate for the approximation of genetic drift models. In this talk we will discuss various genetic drift models (such as the Wright-Fisher model), their approximating Dirichlet distributions, and calculate explicit error bounds for the approximations. If time permits we will cover the Stein's method framework used for the results and offer some insights regarding their derivation.