کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
5129234 1489624 2017 15 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Asymptotics for least product relative error estimation and empirical likelihood with longitudinal data
موضوعات مرتبط
مهندسی و علوم پایه ریاضیات آمار و احتمال
پیش نمایش صفحه اول مقاله
Asymptotics for least product relative error estimation and empirical likelihood with longitudinal data
چکیده انگلیسی

A multiplicative regression model with longitudinal data is introduced, and a least product relative errors estimate is constructed based on relative errors. Generally, the least squares criterion and least absolute deviation criterion based on absolute errors are the most widely used criteria in the regression analysis. However, when response variables have different measurement scales, relative errors may be superior to absolute errors. Thence, we develop a least product relative errors estimator of parameter based on relative errors, and obtain their asymptotic properties where some nuisance parameters such as correlation structure of error terms are included. In addition, block empirical likelihood technique is employed to construct the confidence regions of the corresponding unknown regression parameter, avoiding density estimation. Simulation results confirm that the proposed methods perform well.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of the Korean Statistical Society - Volume 46, Issue 3, September 2017, Pages 375-389
نویسندگان
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