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    政大機構典藏 > 商學院 > 統計學系 > 期刊論文 >  Item 140.119/120426
    Please use this identifier to cite or link to this item: http://nccur.lib.nccu.edu.tw/handle/140.119/120426

    Title: A General Algorithm for Nonparametric Maximum Likelihood Estimator of Stochastically Ordered Survival Functions from Case 2 Interval Censored Data
    Authors: Kim, Yuneung;Son, Won;Lim, Johan;Kuo, H.-C.
    Kuo, H.-C.
    Contributors: 統計系
    Keywords: Interval-censored data;Linear order constraints;Non-parametric maximum likelihood estimator;Quadratic programming;Stochastic ordering
    Date: 2017-10
    Issue Date: 2018-10-09 11:49:53 (UTC+8)
    Abstract: In this paper, we study an algorithm to compute the non-parametric maximum likelihood estimator of stochastically ordered survival functions from case 2 interval-censored data. The algorithm, simply denoted by SQP (sequential quadratic programming), re-parameterizes the likelihood function to make the order constraints as a set of linear constraints, approximates the log-likelihood function as a quadratic function, and updates the estimate by solving a quadratic programming. We particularly consider two stochastic orderings, simple and uniform orderings, although the algorithm can also be applied to many other stochastic orderings. We illustrate the algorithm using the breast cancer data reported in Finkelstein and Wolfe
    Relation: Communications in Statistics - Simulation and Computation,
    Data Type: article
    DOI 連結: https://doi.org/10.1080/03610918.2017.1400052
    DOI: 10.1080/03610918.2017.1400052
    Appears in Collections:[統計學系] 期刊論文

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