Least squares estimators of the regression function with twice censored data

K. Kebabi, I. Laroussi and F. Messaci

Statistics & Probability Letters, 2011, vol. 81, issue 11, 1588-1593

Abstract: We propose least squares estimators of E(Y/X=x) for Y censored on the right by R and min(Y,R) left censored. We establish their convergence in the L2-norm. This work extends a known result in the context of right censoring.

Keywords: Regression; estimators; Least; squares; estimators; Twice; censored; data; Convergence; in; the; L2-norm (search for similar items in EconPapers)
Date: 2011
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Citations: View citations in EconPapers (3)

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