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In this paper we propose a new method for estimating parameters in a single-index model under censoring based on the Beran estimator for the conditional distribution function. This, likelihood-based method is also a useful and simple tool used for bandwidth selection. Additionally, we perform an...
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A new likelihood approach is proposed for the problem of semiparametric estimation of a conditional distribution or density under censoring. Consistency and asymptotic normality for two versions of the maximum likelihood estimator of the parameter vector in the single index model are proved. The...
Persistent link: https://www.econbiz.de/10010594242