Department of Statistics Seminar
North Carolina State University

presents

Dr. Jayanta K. Ghosh

Purdue University/Indian Statistical Institute

"Convergence and Consistency of Newton's Algorithm for Estimating a Mixing Distribution"

ABSTRACT

In recent years Michael Newton has proposed an algorithmic estimate of a mixing distribution , which is computationally efficient.We prove its convergence and consistency under rather strong conditions.The consistency result is new. A proof of convergence given earlier under same conditions by Newton is shown to be incomplete and not easily rectifiable.We study various other aspects of the estimate and compare it with the Bayes estimate based on Dirichlet mixtures.
This is joint work with Surya Tokdar.

Friday, April, 28, 2006

3:35 - 4:35 pm

206 Cox Hall

Refreshments will be served on the second floor of Dabney Hall (left of Room 222) at 3:00 pm.