Online Program Home
My Program

Abstract Details

Activity Number: 188
Type: Contributed
Date/Time: Monday, August 1, 2016 : 10:30 AM to 12:20 PM
Sponsor: International Chinese Statistical Association
Abstract #319345
Title: Properties of Difference-Based Ridge Estimators in Partial Linear Models
Author(s): June Luo*
Companies:
Keywords: partial linear model ; ridge estimator ; large dimension ; curse of dimensionality ; asymptotics
Abstract:

The linear model with a growing number of predictors arises in many contemporary scientific endeavor. In this presentation, we consider the commonly used ridge estimator in partial linear models when a strictly linear model is inadequate given that some of the relations are believed to be of certain linear form while others are not easily parameterized, and thus a semiparametric partial linear model is considered. For these semiparametric partial linear models with p is bigger than n, we develop a procedure to estimate the linear coefficients as if the nonparametric part is not present. The properties of the proposed estimator for the linear component is studied for growing p. Data analysis is presented to support that the proposed estimator of the linear component performs very well.


Authors who are presenting talks have a * after their name.

Back to the full JSM 2016 program

 
 
Copyright © American Statistical Association