Estimation of a general parametric location in censored regression

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 M={m_{θ}:θ ∈ Θ} and we propose a new method for estimating the true unknown value θ_{0}. The method is based on nonparametric imputation for the censored observations. The consistency and asymptotic normality of the proposed estimator are established.

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Document type	Contribution à ouvrage collectif (Book Chapter) – Chapitre
Access type	Accès restreint
Publication date	2012
Language	Anglais
Host document	Ingrid Van Keilegom, Paul W. Wilson ; "Exploring Research Frontiers in Contemporary Statistics and Econometrics"- p. 177-187 (ISBN : 978-3-7908-2348-6)
Publisher	springer-Verlag
Publication status	Publié
Affiliation	UCL - SSH/LIDAM/ISBA - Institut de Statistique, Biostatistique et Sciences Actuarielles
Links	http://hdl.handle.net/2078.1/127111[Handle] https://doi.org/10.1007/978-3-7908-2349-3[DOI]

See also
	[boreal:116747]	Estimation of a general parametric location in censored regression