Some topics on robust nonparametric regression and regression quantiles
Shen, Liji
This item is only available for download by members of the University of Illinois community. Students, faculty, and staff at the U of I may log in with your NetID and password to view the item. If you are trying to access an Illinois-restricted dissertation or thesis, you can request a copy through your library's Inter-Library Loan office or purchase a copy directly from ProQuest.
Permalink
https://hdl.handle.net/2142/22500
Description
Title
Some topics on robust nonparametric regression and regression quantiles
Author(s)
Shen, Liji
Issue Date
1994
Doctoral Committee Chair(s)
Portnoy, Stephen L.
Department of Study
Statistics
Discipline
Statistics
Degree Granting Institution
University of Illinois at Urbana-Champaign
Degree Name
Ph.D.
Degree Level
Dissertation
Keyword(s)
Statistics
Language
eng
Abstract
Local kernel estimates and B-spline estimates are considered in the nonparametric regression and the generalized linear models. The consistency and asymptotic normality of kernel estimates are proved. Simulations on B-spline estimates for nonparametric regression and generalized linear models are provided.
Also a sequential procedure based on the regression quantiles is proposed for constructing a fixed size confidence region of parameters of a linear model. The stopping time is asymptotically efficient and the confidence region is asymptotically consistent.
Use this login method if you
don't
have an
@illinois.edu
email address.
(Oops, I do have one)
IDEALS migrated to a new platform on June 23, 2022. If you created
your account prior to this date, you will have to reset your password
using the forgot-password link below.
