Legend: Boston Convention & Exhibition Center = CC, Westin Boston Waterfront = W, Seaport Boston Hotel = S
A * preceding a session name means that the session is an applied session.
A ! preceding a session name means that the session reflects the JSM meeting theme.
A * preceding a session name means that the session is an applied session.
A ! preceding a session name means that the session reflects the JSM meeting theme.
Activity Details
|
|
Tweet | ||
| CE_05C | Sat, 8/2/2014, 8:30 AM - 5:00 PM | CC-160A | |
| Quantile Regression — Professional Development Continuing Education Course | |||
| ASA , Biometrics Section | |||
| Quantile regression is a valuable alternative to classical least squares regression. Instead of modeling the conditional functions, quantile regression offers a variety of methods for estimating conditional quantile functions. In many applications such as birth weight studies, survival analysis, climate studies and so on, the covariates may have different impacts on different tails of the response distribution. Quantile regression enables the researcher to explore more thoroughly heterogeneous covariate effects, and study the tails of scientific interest. The course will offer a comprehensive introduction to quantile regression methods and briefly survey some recent developments. The first part of the course will introduce basics of quantile regression, including its features, comparison with the least squares regression, estimation and computation, statistical properties and inferential procedures. Methods will be demonstrated by using examples from birthweight, climate and survival studies. The second part of the course will discuss more advanced topics including nonparametric quantile regression, quantile regression for longitudinal and time series data, censored quantile regression and survival analysis, and so on. Course lectures will be complemented by a computationally oriented interlude using R language. Thus it would be helpful if students brought laptops equipped with R and quantreg package already installed. | |||
| Instructor(s): Roger Koenker, University of Illinois at Urbana-Champaign, Huixia Judy Wang, North Carolina State University | |||
2014 JSM Online Program Home
For information, contact jsm@amstat.org or phone (888) 231-3473.
If you have questions about the Professional Development program, please contact the Education Department.
The views expressed here are those of the individual authors and not necessarily those of the JSM sponsors, their officers, or their staff.
Copyright © American Statistical Association.