کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
1154794 | 958411 | 2006 | 8 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Nonparametric estimation for quadratic regression
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موضوعات مرتبط
مهندسی و علوم پایه
ریاضیات
آمار و احتمال
پیش نمایش صفحه اول مقاله
چکیده انگلیسی
The method of least squares provides the most widely used algorithm for fitting a linear model. A variety of nonparametric procedures have been developed that are designed to be robust against model violations and resistant against aberrant points. One such method introduced by Theil [1950. A rank-invariant method of linear and polynomial regression analysis. I, II, III. Proc. Ned. Akad. Wet. 53, 386–392, 521–525, 1397–1412] is based on pairwise estimates. There are many examples in which the data are nonlinear, and in particular, where a quadratic fit may be more appropriate. We here propose a nonparametric method for fitting a quadratic regression.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Statistics & Probability Letters - Volume 76, Issue 11, 1 June 2006, Pages 1156–1163
Journal: Statistics & Probability Letters - Volume 76, Issue 11, 1 June 2006, Pages 1156–1163
نویسندگان
Samprit Chatterjee, Ingram Olkin,