کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
415573 | 681214 | 2007 | 10 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
The Koul–Susarla–Van Ryzin and weighted least squares estimates for censored linear regression model: A comparative study
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
نظریه محاسباتی و ریاضیات
پیش نمایش صفحه اول مقاله
![عکس صفحه اول مقاله: The Koul–Susarla–Van Ryzin and weighted least squares estimates for censored linear regression model: A comparative study The Koul–Susarla–Van Ryzin and weighted least squares estimates for censored linear regression model: A comparative study](/preview/png/415573.png)
چکیده انگلیسی
The Koul–Susarla–Van Ryzin (KSV) and weighted least squares (WLS) methods are simple to use techniques for handling linear regression models with censored data. They do not require any iterations and standard computer routines can be employed for model fitting. Emphasis has been given to the consistency and asymptotic normality for both estimators, but the finite sample performance of the WLS estimator has not been thoroughly investigated. The finite sample performance of these two estimators is compared using an extensive simulation study as well as an analysis of the Stanford heart transplant data. The results demonstrate that the WLS approach performs much better than the KSV method and is reliable for use with censored data.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Computational Statistics & Data Analysis - Volume 51, Issue 12, 15 August 2007, Pages 6488–6497
Journal: Computational Statistics & Data Analysis - Volume 51, Issue 12, 15 August 2007, Pages 6488–6497
نویسندگان
Yanchun Bao, Shuyuan He, Changlin Mei,