Semiparametric estimation of censored transformation models

Tue Gørgens*

*Corresponding author for this work

    Research output: Contribution to journalArticlepeer-review

    3 Citations (Scopus)


    Many widely used models, including proportional hazards models with unobserved heterogeneity, can be written in the form Λ(Y) = min [β′X + U, C], where Λ is an unknown increasing function, the error term U has unknown distribution function Ψ and is independent of X, C is a random censoring threshold and U and C are conditionally independent given X. This paper develops new n1/2-consistent and asymptotically normal semiparametric estimators of Λ and Ψ which are easier to use than previous estimators. Moreover, Monte Carlo results suggest that the mean integrated squared error of predictions based on the new estimators is lower than for previous estimators.

    Original languageEnglish
    Pages (from-to)377-393
    Number of pages17
    JournalJournal of Nonparametric Statistics
    Issue number3
    Publication statusPublished - Jun 2003


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