JSM 2015 Preliminary Program

Online Program Home
My Program

Abstract Details

Activity Number: 28
Type: Contributed
Date/Time: Sunday, August 9, 2015 : 2:00 PM to 3:50 PM
Sponsor: IMS
Abstract #315086 View Presentation
Title: Weighted Bootstrap and Kernel Density Estimation
Author(s): Bo Liu* and Majid Mojirsheibani
Companies: and California State University at Northridge
Keywords: Kernel ; Density ; CLT ; Brownian bridge ; KMT-type approximation ; Bootstrap
Abstract:

A weighted bootstrap method is considered to approximate the distribution of the Lp norms of kernel density estimates. Here p is not restricted to be 1 or 2, and can be any number in [1, ?). Using a KMT-type approximation for the weighted bootstrap processes by a sequence of Brownian bridges, due to Horvath et al. (2000), we establish an unconditional bootstrap central limit theorem for these Lp statistics. Furthermore, through simulation studies, it will be shown that, depending on the weights chosen, the proposed approximation can outperform both the classical large-sample theory as well as Efron's (1979) original bootstrap algorithm.


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

Back to the full JSM 2015 program





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