scholarly journals Global Bahadur Representation for Nonparametric Censored Regression Quantiles and its Applications

2011 ◽  
Author(s):  
Oliver B. Linton ◽  
Efang Kong ◽  
Yingcun Xia
Keyword(s):  
Censored Regression ◽  
Bahadur Representation ◽  
Regression Quantiles

scholarly journals Censored regression quantiles with endogenous regressors

2007 ◽  
Vol 141 (1) ◽  
pp. 65-83 ◽  
Author(s):  
Richard Blundell ◽  
James L. Powell
Keyword(s):  
Censored Regression ◽  
Regression Quantiles ◽  
Endogenous Regressors

Simple resampling methods for censored regression quantiles

2000 ◽  
Vol 99 (2) ◽  
pp. 373-386 ◽  
Author(s):  
Yannis Bilias ◽  
Songnian Chen ◽  
Zhiliang Ying
Keyword(s):  
Censored Regression ◽  
Resampling Methods ◽  
Regression Quantiles

Censored regression quantiles

1986 ◽  
Vol 32 (1) ◽  
pp. 143-155 ◽  
Author(s):  
James L. Powell
Keyword(s):  
Censored Regression ◽  
Regression Quantiles

scholarly journals Regression Quantile Analysis of Claim Termination Rates for Income Protection Insurance

2006 ◽  
Vol 1 (2) ◽  
pp. 345-357 ◽  
Author(s):  
D. G. W. Pitt
Keyword(s):  
Censored Regression ◽  
Regression Quantiles ◽  
Regression Quantile

ABSTRACTThis paper investigates the use of censored regression quantiles in the analysis of claim termination rates for income protection (IP) insurance. The paper demonstrates the importance of modeling quantiles given the growing interest of regulators and others in stochastic approaches to valuation of insurance liabilities and risk margins.

Correction to Censored Regression Quantiles by S. Portnoy, 98 (2003), 1001–1012

2006 ◽  
Vol 101 (474) ◽  
pp. 860-861 ◽  
Author(s):  
Tereza Neocleous ◽  
Karlien Vanden Branden ◽  
Stephen Portnoy
Keyword(s):  
Censored Regression ◽  
Regression Quantiles

scholarly journals GLOBAL BAHADUR REPRESENTATION FOR NONPARAMETRIC CENSORED REGRESSION QUANTILES AND ITS APPLICATIONS

2013 ◽  
Vol 29 (5) ◽  
pp. 941-968 ◽  
Author(s):  
Efang Kong ◽  
Oliver Linton ◽  
Yingcun Xia
Keyword(s):  
Regression Models ◽  
Asymptotic Properties ◽  
Gradient Vector ◽  
Bahadur Representation ◽  
Response Variable ◽  
Regression Quantiles ◽  
Uniform Convergence Rate ◽  
Strong Uniform Convergence ◽  
Theoretical Analyses ◽  
Average Derivative

This paper is concerned with the nonparametric estimation of regression quantiles of a response variable that is randomly censored. Using results on the strong uniform convergence rate of U-processes, we derive a global Bahadur representation for a class of locally weighted polynomial estimators, which is sufficiently accurate for many further theoretical analyses including inference. Implications of our results are demonstrated through the study of the asymptotic properties of the average derivative estimator of the average gradient vector and the estimator of the component functions in censored additive quantile regression models.

Asymptotics for censored regression quantiles

2010 ◽  
Vol 22 (1) ◽  
pp. 115-130 ◽  
Author(s):  
Stephen Portnoy ◽  
Guixian Lin
Keyword(s):  
Censored Regression ◽  
Regression Quantiles
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