Guided Censored Regression | Zendy

Talamakrouni Majda | Zendy; Ghouch Anouar El | Zendy; Van Keilegom Ingrid | Zendy

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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.

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