Identifiability conditions for the linear regression model under right censoring-Reference-Cited by-同舟云学术

Identifiability conditions for the linear regression model under right censoring

Published:2020-03-25 Issue:1 Volume:51 Page:116-134
ISSN:0361-0926
Container-title:Communications in Statistics - Theory and Methods
language:en
Short-container-title:Communications in Statistics - Theory and Methods

Author:

Yu Qiqing¹,Dong Junyi²

Affiliation:

1. Department of Mathematical Sciences, SUNY, Binghamton, New York, USA

2. Math and Statistics Department, St. Ambrose University, Davenport, Iowa, USA

Publisher

Informa UK Limited

Subject

Statistics and Probability

Link

https://www.tandfonline.com/doi/pdf/10.1080/03610926.2020.1743315

Reference9 articles.

1. Linear regression with censored data

2. Dong, J. Y., and Q. Q. Yu. 2020. Technical Report on “Identifiability Conditions for the Linear Regression Model under Right Censoring”. http://people.math.binghamton.edu/qyu/ftp/tech_cbje.pdf

3. A Lack-of-Fit Test for Quantile Regression

4. Large Sample Theory of a Modified Buckley-James Estimator for Regression Analysis with Censored Data

5. A quantile regression estimator for censored data

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