Masters Project Defence “Expectation-Maximization Algorithm for the Analysis of Missing Data” | Department of Mathematics

Masters Project Defence “Expectation-Maximization Algorithm for the Analysis of Missing Data”

Event Information
Event Location: 
Curry Hall #203
Event Date: 
Wednesday, March 26, 2014 - 11:00am

Professor Kai-Sheng Song invites you to attend the Masters project defense of Yaya Traore next Wednesday, March 26th, at 11:00 am in Curry Hall room 203. Cookies and coffee will be served in GAB 472 following this event.

"Expectation-Maximization Algorithm for the Analysis of Missing Data"

Abstract: Expectation-Maximization (EM) algorithm is one of the most widely-used computational method in statistics. It is an iterative procedure for finding maximum likelihood estimates of parameters of a statistical model when maximizing the likelihood function is difficult or when the data is incomplete (missing).

In this talk, we present the EM algorithm for the analysis of missing data and demonstrate its convergence properties both numerically and theoretically.