Empirical likelihood for semiparametric regression model with missing response data

Xue Liugen

Chinese︱Feedback︱Save this page

• Elaborating Academic Views 　　　　 • Exchanging Innovative Ideas
• Protecting Intellectual Properties 　　• Fast Sharing Science Papers

Sponsored by the Center for Science and Technology Development of the Ministry of Education
Supervised by Ministry of Education of the People's Republic of China

Home > Papers

Empirical likelihood for semiparametric regression model with missing response data

Xue Liugen * #

College of Applied Sciences, Beijing University of

*Correspondence author

#Submitted by

Subject:

Funding: 高等学校博士学科点专项科研基金,国家自然科学基金,北京市自然科学基金（No.20070005003,10871013,1072004）

Opened online: 3 March 2009

Accepted by: none

Citation: Xue Liugen.Empirical likelihood for semiparametric regression model with missing response data[OL]. [ 3 March 2009] http://en.paper.edu.cn/en_releasepaper/content/29843

A bias-corrected technique for constructing empirical likelihood ratio is used to study a semiparametric regression model with missing response data. We are interested in inference for the regression coefficients, the baseline function and the response mean. A class of empirical likelihood ratio functions for the parameters of interest are defined so that the undersmoothing for estimating the baseline function is avoided, and the existing data-driven algorithm is also valid for selecting an optimal bandwidth. Our approach is to directly calibrate the empirical log-likelihood ratio so that the resulting ratio is asymptotically chi-squared. Also, a class of estimators for the parameters of interest are constructed, their asymptotic distributions are obtained, and the consistent estimators of asymptotic bias and variance are provided. Our results can be used to construct the confidence intervals for the parameters of interest. A simulation study is undertaken to compare the empirical likelihood with the normal approximation-based method in terms of coverage accuracies and average lengths of confidence intervals.

Keywords:Confidence interval;Empirical likelihood;Missing response data; Regression coefficient;Semiparametric regression model

For this paper

● PDF (0B)
● Revision 0 　　
● Print this paper
● Recommend this paper to a friend
● Add to my favorite list

Saved Papers

Please enter a name for this paper to be shown in your personalized Saved Papers list

Tags

Add yours

Related Papers

Other papers by Liugen CHU

Statistics

PDF Downloaded	400
Bookmarked	0
Recommend	5
Comments	Array

Submit your papers

Alert Name:
Alerting to:
Authentication email will be sent to your email address in 24 hours
Frequency:
Email Message Format:	Plain text Graphical(HTML)

Complete the form below and we will recommend the selected titles to your friends on your behalf. * Indicates a required field.
Your name*:
Your email address*:
Recipient's name*:
Recipient's email address*:
(multiple recipient's names and email addresses should be separated with semicolons)
Your comments:	I thought you would find the page(s) useful.

Your name:
Your email address:
Recipient's name:
Recipient's email address:
(multiple recipient's names and email addresses should be separated with semicolons)
Your comments:	I thought you would find this page useful.

Disclaimer: This message was sent to your friend using the "Send it to a friend" facility on the Sciencepaper Online’ WWW site, http://www.paper.edu.cn/en. The Sciencepaper Online is not responsible for the content of this email, and anything said in this email does not necessarily reflect the Sciencepaper Online's views.

	Check out RSS, or use RSS reader to subscribe this item

Saved Papers