JSM 2015 Online Program

Online Program Home
My Program

Legend: Washington State Convention Center = CC, Sheraton Seattle = S, Grand Hyatt = GH and The Conference Center = TCC
* = applied session       ! = JSM meeting theme

Activity Details

CE_19C Tue, 8/11/2015, 8:00 AM - 12:00 PM S-Willow B
Quantile Regression in Practice (ADDED FEE) — Professional Development Continuing Education Course
Quantile regression is a modern statistical approach for modeling the quantiles of a response variable conditional on explanatory covariates. Compared with ordinary least squares linear regression (which models the conditional mean), quantile regression enables you to more fully explore your data by modeling a set of conditional quantiles, such as the median and 5th and 95th percentiles. Quantile regression is particularly useful when your data are heterogeneous, or when you cannot assume a parametric distribution for the response. Quantile process regression fits quantile regression models for the entire range of quantile levels in [0,1] and enables you to estimate the conditional distribution of a response variable. Applications include risk analysis, conditional ranking, and sample selection. This tutorial provides an overview of the theoretical concepts of quantile regression and emphasizes its practical benefits as both a regression method and distribution estimation method. This tutorial uses a variety of examples to illustrate the following topics: 1. motivation for and basic concepts of quantile regression, 2. comparison of quantile regression with linear regression, 3. inference with quantile regression, 4. quantile process regression, and 5. model selection for quantile regression. Participants are assumed to be familiar with linear algebra and linear regression. Computations are done with SAS.
Instructor(s): Yonggang Yao, SAS Institute

For program information, contact the JSM Registration Department or phone (888) 231-3473.

For Professional Development information, 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.

2015 JSM Online Program Home