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Guided Censored Regression
Author(s) -
Talamakrouni Majda,
Ghouch Anouar El,
Van Keilegom Ingrid
Publication year - 2015
Publication title -
scandinavian journal of statistics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.359
H-Index - 65
eISSN - 1467-9469
pISSN - 0303-6898
DOI - 10.1111/sjos.12103
Subject(s) - mathematics , estimator , statistics , censored regression model , parametric statistics , regression , minimum variance unbiased estimator , regression analysis , bias of an estimator , nonparametric regression , variance (accounting) , variance function , linear regression , accounting , business
Parametrically guided non‐parametric regression is an appealing method that can reduce the bias of a non‐parametric regression function estimator without increasing the variance. In this paper, we adapt this method to the censored data case using an unbiased transformation of the data and a local linear fit. The asymptotic properties of the proposed estimator are established, and its performance is evaluated via finite sample simulations.