The likelihood function for the bivariate survivor function F, under independent censorship, is maximized to obtain a non-parametric maximum likelihood estimator F K . F K may or may not be unique depending on the con"guration of singly-and doubly-censored pairs. The likelihood function can be maxim
β¦ LIBER β¦
A non-parametric maximum likelihood estimator for bivariate interval censored data
β Scribed by Rebecca A. Betensky; Dianne M. Finkelstein
- Publisher
- John Wiley and Sons
- Year
- 1999
- Tongue
- English
- Weight
- 106 KB
- Volume
- 18
- Category
- Article
- ISSN
- 0277-6715
No coin nor oath required. For personal study only.
β¦ Synopsis
We derive a non-parametric maximum likelihood estimator for bivariate interval censored data using standard techniques for constrained convex optimization. Our approach extends those taken for univariate interval censored data. We illustrate the estimator with bivariate data from an AIDS study.
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