Estimation Precision in a Quantile Regression Model

Student Author(s)

Jiyi Jiang

Faculty Mentor(s)

Dr. Yew Meng Koh

Document Type

Poster

Event Date

4-15-2016

Abstract

Quantile regression provides a method for estimating quantiles of a distribution while incorporating covariate information. If distributional assumptions are placed on the distribution of the response variable, an asymptotic variance estimate for the estimators can be obtained. This is done for a variety of distributions and comparisons are made to equivalent simple linear regression models.

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Comments

This research supported by the Tanis Math Research Fund.