CHINESE JOURNAL OF APPLIED PROBABILITY AND STATIST 2013, 29(3) 246-260 DOI:      ISSN: 1001-4268 CN: 31-1256

Current Issue | Archive | Search                                                            [Print]   [Close]
article
Information and Service
This Article
Supporting info
PDF(234KB)
[HTML]
Reference
Service and feedback
Email this article to a colleague
Add to Bookshelf
Add to Citation Manager
Cite This Article
Email Alert
Keywords
Authors
PubMed

Variable Selection for the Linear EV Model with Longitudinal Data

Tian Ruiqin, Xue Liugen

College of Applied Sciences, Beijing University of Technology

Abstract��

In this paper, we focus on the variable
selection for the linear EV model with longitudinal data when some
covariates are measured with errors. A new bias-corrected variable
selection procedure is proposed based on the combination of the
quadratic inference functions and shrinkage estimations. With
appropriate selection of the tuning parameters, we establish the
consistency and asymptotic normality of the resulting estimators.
Extensive Monte Carlo simulation studies are conducted to examine
the finite sample performance of the proposed variable selection
procedures.

Keywords��
Received  Revised  Online:  
DOI:
Fund:
Corresponding Authors: Tian Ruiqin
Email:
About author:

References��
Similar articles

Copyright by CHINESE JOURNAL OF APPLIED PROBABILITY AND STATIST