Log-Exponentiated Frechet regression model with censored data

被引：0
|
作者：
Al-Amoudi, Hanan H. [1 ]
Mousa, Salwa A. [1 ,2 ]
Baharith, Lamya A. [1 ]
机构：
[1] King Abdulaziz Univ, Fac Sci, Dept Stat, Jeddah 21413, Saudi Arabia
[2] Al Azhar Univ, Fac Commerce, Girls Campus, Nasr City, Cairo, Egypt
来源：
INTERNATIONAL JOURNAL OF ADVANCED AND APPLIED SCIENCES | 2016年 / 3卷 / 06期
关键词：
Exponentiated Frechet distribution; Regression model; Maximum likelihood; Jackknife method; Residual analysis; Global influences;
D O I：
暂无
中图分类号：
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号：
07 ; 0710 ; 09 ;
摘要：
In this article, we propose the log-exponentiated Frechet regression model based on exponentiated Frechet distribution. Maximum likelihood and jackknife methods are used to estimate the Proposed model parameters based on censored data. Model assumptions are checked using martingale and deviance residuals. Moreover, global influence is used to detect influential observations. The behavior of the maximum likelihood and jackknife estimators is investigated through Monte Carlo simulation. The empirical distribution of the martingale and deviance residuals of the proposed model is examined. Leukemia data is analyzed to show the flexibility of the proposed model. (C) 2016 IASE Publisher. All rights reserved.
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页码：1 / 9
页数：9
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