Colloquium

Thursday, Nov.13, 2007

4:00 PM, BAC 219

Speaker: Xuming He, University of Illinois at Urbana-Champaign

Hosts: Vasant Waikar and Doug Noe

Title: Recent Developments on Quantile Regression

Abstract: Quantile regression models are increasingly popular in a wide range of applications.

It is easy to argue that the usual regression models that focus on conditional means are often

inadequate to reflect inhomogeneity or to capture some interesting part of the population. As the

quantile regression approach gains popularity in the econometrics, statistics and biostatistics

literature, it is important that we have reliable inference tools. In this talk, I will review a number

of existing methods for estimating standard errors and for constructing confidence intervals, and

explain why it has been difficult for software developers to choose a default method. I will then

introduce the Markov chain marginal bootstrap (MCMB) algorithm, and assess its performance

in terms of accuracy, speed, and reliability. The MCMB algorithm is not about Bayesian computation,

but it is especially appealing for handling high dimensional problems. The current version of the

MCMB algorithm for quantile regression is available as an R package or a SAS procedure.


Bio: Xuming He is Professor of Statistics, and Jerry and Ann Nerad Professorial Scholar at the

University of Illinois at Urbana-Champaign (UIUC). Upon obtaining his PhD from UIUC in 1989,

he taught statistics at the National University of Singapore (1989-1993) before returning to

join the UIUC faculty. Since 1993, He has held visiting positions at the Argonne National
Laboratory,  the University of Hong Kong, and the M.D. Anderson Cancer Center in Houston

for research in statistics and related areas. From 2003 to 2005, he served as a Program Director

of Statistics at the National Science Foundation.

His research interests include robust statistics, semiparametric models, dimension reduction,
and applications of statistics in genomics, engineering, education testing, health sciences, and

geosciences.

He is an elected Fellow of the Institute of Mathematical Statstics (IMS) and of the American

Statistical Association (ASA). He is currently Editor of the IMS Bulletin, and on the editorial

boards of a number of statistics journals including JASA and Annals of Statistics. He has taught

a wide range of statistics courses, supervised more than a dozen doctoral students, and appears
regularly in the Incomplete List of Teachers Rated as Excellent by students at UIUC.