Estimation of a General Parametric Location in Censored Regression

Cédric Heuchenne () and Ingrid Van Keilegom ()
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Cédric Heuchenne: HEC-Management School of University of Liége, QuantOM (Centre for Quantitative Methods and Operations Management)
Ingrid Van Keilegom: Université catholique de Louvain, Institut de statistique, biostatistique et sciences actuarielles

Chapter Chapter 8 in Exploring Research Frontiers in Contemporary Statistics and Econometrics, 2011, pp 177-187 from Springer

Abstract: Abstract Consider the random vector (X, Y ), where Y represents a response variable and X an explanatory variable. The response Y is subject to random right censoring, whereas X is completely observed. Let m(x) be a conditional location function of Y given X = x. In this paper we assume that m( ⋅) belongs to some parametric class $$\mathcal{M} =\{ {m}_{\theta } : \theta \in \Theta \}$$ and we propose a new method for estimating the true unknown value θ0. The method is based on nonparametric imputation for the censored observations. The consistency and asymptotic normality of the proposed estimator are established.

Keywords: General Location Parameter; Censored Regression; Censored Observations; Nonparametric Imputation; Unknown True Value (search for similar items in EconPapers)
Date: 2011
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-7908-2349-3_8

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DOI: 10.1007/978-3-7908-2349-3_8

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