Single-index Regression models with right-censored responses
| dc.creator | Lopez, Olivier | |
| dc.date | 2008-03-07 | |
| dc.date.accessioned | 2026-07-07T12:17:29Z | |
| dc.date.available | 2026-07-07T12:17:29Z | |
| dc.description | In this article, we propose some new generalizations of M-estimation procedures for single-index regression models in presence of randomly right-censored responses. We derive consistency and asymptotic normality of our estimates. The results are proved in order to be adapted to a wide range of techniques used in a censored regression framework (e.g. synthetic data or weighted least squares). As in the uncensored case, the estimator of the single-index parameter is seen to have the same asymptotic behavior as in a fully parametric scheme. We compare these new estimators with those based on the average derivative technique of Burke and Lu (2005) through a simulation study. | |
| dc.identifier | https://arxiv.org/abs/0803.1112 | |
| dc.identifier | http://arxiv.org/abs/0803.1112 | |
| dc.identifier.uri | http://salesiana.dossiersoluciones.com/handle/123456789/212093 | |
| dc.subject | Statistics Theory | |
| dc.subject | 62N01, 62N02, 62G08, 62G20 | |
| dc.title | Single-index Regression models with right-censored responses | |
| dc.type | text |