Tsui, Kwok-Leung; Jewell, Nicholas P.; Wu, C. F. J. A nonparametric approach to the truncated regression problem. (English) Zbl 0662.62040 J. Am. Stat. Assoc. 83, No. 403, 785-792 (1988). A description is given of a new method of estimating the regression parameters in the linear regression model from data where the dependent variable is subject to truncation. The residual distribution is allowed to be unspecified. The method is iterative and involves estimation of the residual distribution under the truncated sampling scheme. The technique can be interpreted as an iterative bias adjustment of the observations in order to correct the regression relationship in the sampled population to match that of the model. A simulation study compares the performance of various estimators. Cited in 2 ReviewsCited in 13 Documents MSC: 62G05 Nonparametric estimation 62J05 Linear regression; mixed models Keywords:least squares; weighted median; truncation; estimation of the residual distribution; iterative bias adjustment; simulation study PDFBibTeX XMLCite \textit{K.-L. Tsui} et al., J. Am. Stat. Assoc. 83, No. 403, 785--792 (1988; Zbl 0662.62040) Full Text: DOI