A Non-Mixture Cure Model for Right-Censored Data with Frechet Distribution

被引：8

作者：

Kutal, Durga H. ^{[1
,2
]}

Qian, Lianfen ^{[1
,3
]}

机构：

[1] Florida Atlantic Univ, Dept Math Sci, Boca Raton, FL 33431 USA

[2] Wake Forest Univ, Winston Salem, NC 27101 USA

[3] Wenzhou Univ, Wenzhou, Peoples R China

来源：

STATS | 2018年 / 1卷 / 01期

关键词：

Non-mixture model; Frechet distribution; Right-censored survival data; Maximum likelihood method;

D O I：

10.3390/stats1010013

中图分类号：

O1 [数学];

学科分类号：

0701 ; 070101 ;

摘要：

This paper considers a non-mixture cure model for right-censored data. It utilizes the maximum likelihood method to estimate model parameters in the non-mixture cure model. The simulation study is based on Frechet susceptible distribution to evaluate the performance of the method. Compared with Weibull and exponentiated exponential distributions, the non-mixture Frechet distribution is shown to be the best in modeling a real data on allogeneic marrow HLA-matched donors and ECOG phase III clinical trial e1684 data.

引用

页码：176 / 188

页数：13

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