کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
1149023 | 957860 | 2012 | 17 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Likelihood-based approaches for multivariate linear models under inequality constraints for incomplete data
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
ریاضیات
ریاضیات کاربردی
پیش نمایش صفحه اول مقاله

چکیده انگلیسی
In this paper, we consider a multivariate linear model with complete/incomplete data, where the regression coefficients are subject to a set of linear inequality restrictions. We first develop an expectation/conditional maximization (ECM) algorithm for calculating restricted maximum likelihood estimates of parameters of interest. We then establish the corresponding convergence properties for the proposed ECM algorithm. Applications to growth curve models and linear mixed models are presented. Confidence interval construction via the double-bootstrap method is provided. Some simulation studies are performed and a real example is used to illustrate the proposed methods.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Statistical Planning and Inference - Volume 142, Issue 11, November 2012, Pages 2926–2942
Journal: Journal of Statistical Planning and Inference - Volume 142, Issue 11, November 2012, Pages 2926–2942
نویسندگان
Shurong Zheng, Jianhua Guo, Ning-Zhong Shi, Guo-Liang Tian,