English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

In this article, we propose some new generalizations of M-estimationprocedures for single-index regression models in presence of randomlyright-censored responses. We derive consistency and asymptotic normality of ourestimates. The results are proved in order to be adapted to a wide range oftechniques used in a censored regression framework (e.g. synthetic data orweighted least squares). As in the uncensored case, the estimator of thesingle-index parameter is seen to have the same asymptotic behavior as in afully parametric scheme. We compare these new estimators with those based onthe average derivative technique of Burke and Lu (2005) through a simulationstudy.

Single-index Regression models with right-censored responses