Single index regression models with randomly left-truncated data
Statistics Theory
2018-01-22 v1 Probability
Statistics Theory
Abstract
In this paper, based on the kernel estimator proposed by Ould-Said and Lemdani (Ann. Instit. Statist. Math. 2006), we develop some new generalized M-estimator procedures for single index regression models with left-truncated responses. The consistency and asymptotic normality of our estimators are also established. Some simulation studies are given to investigate the finite sample performance of the proposed estimators.
Cite
@article{arxiv.1801.06319,
title = {Single index regression models with randomly left-truncated data},
author = {Kong Lingtao and Zhang Yanli and Dai Hongshuai},
journal= {arXiv preprint arXiv:1801.06319},
year = {2018}
}
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17 pages