ISSN:
1572-9249
Keywords:
censored data
;
Kaplan-Meier product limit estimates
;
Kuhn-Tucker vectors
;
order restrictions
;
stochastic ordering
Source:
Springer Online Journal Archives 1860-2000
Topics:
Mathematics
Notes:
Abstract Stochastic ordering of survival functions is a useful concept in many areas of statistics, especially in nonparametric and order restricted inferences. In this paper we introduce an algorithm to compute maximum likelihood estimates of survival functions where both upper and lower bounds are given. The algorithm allows censored survival data. In a simulation study, we found that the proposed estimates are more efficient than the unrestricted Kaplan-Meier product limit estimates both with and without censored observations.
Type of Medium:
Electronic Resource
URL:
http://dx.doi.org/10.1023/A:1009639318201
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