کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
1149677 | 957892 | 2009 | 15 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Asymptotic normality in partial linear models based on dependent errors
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
ریاضیات
ریاضیات کاربردی
پیش نمایش صفحه اول مقاله
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چکیده انگلیسی
In this paper we are concerned with the regression model yi=xiβ+g(ti)+Vi(1⩽i⩽n) under correlated errors Vi=Ïiei and Vi=âj=-ââcjei-j, where the design points (xi,ti) are known and nonrandom, the slope parameter β and the nonparametric component g are unknown, {ei,Fi} are martingale differences. For the first case, it is assumed that Ïi2=f(ui),ui are known and nonrandom, f is unknown function, we study the issue of asymptotic normality for two different slope estimators: the least squares estimator and the weighted least squares estimator. For the second case, we consider the asymptotic normality of the least squares estimator of β. Also, the asymptotic normality of the nonparametric estimators of g(·) under the two cases are considered.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Statistical Planning and Inference - Volume 139, Issue 4, 1 April 2009, Pages 1357-1371
Journal: Journal of Statistical Planning and Inference - Volume 139, Issue 4, 1 April 2009, Pages 1357-1371
نویسندگان
Han-Ying Liang, Bing-Yi Jing,