Estimation of single-index models with fixed censored responses

Hailin Huang, Yuanzhang Li, Hua Liang, Yanlin Tang

Research output: Contribution to journalArticlepeer-review

2 Scopus citations


We propose a new procedure to estimate the index parameter and link function of single-index models, where the response variable is subject to fixed censoring. Under some regularity conditions, we show that the estimated index parameter is root-n consistent and asymptotically normal, and the estimated nonparametric link function achieves the optimal convergence rate and is asymptotically normal. In addition, we propose a linearity testing method for the nonparametric link function. A simulation study shows that the proposed procedures perform well in finite-sample experiments. An application to an HIV data set is presented for illustrative purposes.
Original languageEnglish (US)
Pages (from-to)829-843
Number of pages15
JournalStatistica Sinica
Issue number2
StatePublished - Apr 2020
Externally publishedYes

ASJC Scopus subject areas

  • Statistics and Probability
  • Statistics, Probability and Uncertainty


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