The Annals of Statistics

Asymptotic theory for nonparametric estimation of survival curves under order restrictions

Jian Huang and Jens Thomas Præstgaard

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Abstract

We consider two problems in nonparametric survival analysis under the restriction of stochastic ordering. The first problem is that of estimating a survival function $\overline{F}(t)$ under the restriction $\overline{F}(t) \geq $\overline{F}_0 (t)$, all t, where $\overline{F}_0 (t)$ is known. The second problem consists of estimating two unknown survival functions $\overline{F}^{(1)}(t)$ and $\overline{F}^{(2)}(t)$ when it is known that $\overline{F}^{(1)}(t) \geq \overline{F}^{(2)}(t)$, all t. The nonparametric maximum likelihood estimators in these problems were derived by Brunk, Franck, Hansen and Hogg and Dykstra. In the present paper we derive their large-sample distributions. We present two sets of proofs depending on whether or not the data are right-censored. When centered and scaled by $n^{1/2}$, the estimators converge in distribution to limiting processes related to the concave majorant of Brownian motion. The limiting distributions are not known in closed form, but can be simulated for the purpose of forming asymptotic pointwise confidence limits.

Article information

Source
Ann. Statist., Volume 24, Number 4 (1996), 1679-1716.

Dates
First available in Project Euclid: 17 September 2002

Permanent link to this document
https://projecteuclid.org/euclid.aos/1032298291

Digital Object Identifier
doi:10.1214/aos/1032298291

Mathematical Reviews number (MathSciNet)
MR1416656

Zentralblatt MATH identifier
0896.62044

Subjects
Primary: 60E20 62J02: General nonlinear regression
Secondary: 60E12

Keywords
Order restrictions nonparametric survival analysis concave majorant

Citation

Præstgaard, Jens Thomas; Huang, Jian. Asymptotic theory for nonparametric estimation of survival curves under order restrictions. Ann. Statist. 24 (1996), no. 4, 1679--1716. doi:10.1214/aos/1032298291. https://projecteuclid.org/euclid.aos/1032298291


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