Extending the iterative convex minorant algorithm to the Cox model for interval-censored data

被引：101

作者：

Pan, W ^{[1
]}

机构：

[1] Univ Minnesota, Div Biostat, Minneapolis, MN 55455 USA

来源：

JOURNAL OF COMPUTATIONAL AND GRAPHICAL STATISTICS | 1999年 / 8卷 / 01期

关键词：

cross-validation; EM; generalized gradient projection; ICM; interval censoring; isotonic regression; Lasso; NPMLE;

D O I：

10.2307/1390923

中图分类号：

O21 [概率论与数理统计]; C8 [统计学];

学科分类号：

020208 ; 070103 ; 0714 ;

摘要：

The iterative convex minorant (ICM) algorithm proposed by Groeneboom and Wellner is fast in computing the NPMLE of the distribution function for interval censored data without covariates. We reformulate the ICM as a generalized gradient projection method (GGP), which leads to a natural extension to the Cox model. It is also easily extended to support Tibshirani's Lasso method. Some simulation results are also shown. For illustration we reanalyze two real datasets.

引用

页码：109 / 120

页数：12

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