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Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/6389

Title: A new, fast algorithm to find the regions of possible support for bivariate interval-censored data
Authors: Bogaerts, Kris
LESAFFRE, Emmanuel
Issue Date: 2004
Publisher: American Statistical Association
Citation: Journal of computational and graphical statistics, 13(2). p. 330-340
Abstract: The estimation of the nonparametric maximum likelihood estimate (NPMLE) of the bivariate distribution function on interval-censored data is a recent topic of research. Among other things, it provides a basic tool for checking a parametric model for the bivariate failure times. As a first step in the estimation of the NPMLE for bivariate interval-censored data, the regions of possible support-that is, the rectangles with nonzero mass-are calculated. For this step a new, fast algorithm is introduced here and compared with two existing algorithms. The advantages of our algorithm will be illustrated on the emergence times of permanent teeth on data from the longitudinal Signal(R) Tandmobiel study.
URI: http://hdl.handle.net/1942/6389
DOI: 10.1198/1061860043371
ISI #: 000221768700004
ISSN: 1061-8600
Category: A1
Type: Journal Contribution
Appears in Collections: Research publications

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