Let us consider the ΓΏxed regression model, Yt = m(xt) + t ; t = 1; : : : ; n; and assume that the random errors, { t }; follow an ARMA-type dependence structure. The purpose of this paper is to study the application of the bootstrap test to check that the unknown regression function, m, follows a ge
β¦ LIBER β¦
Local Linear M-estimation in non-parametric spatial regression
β Scribed by Zhengyan Lin; Degui Li; Jiti Gao
- Book ID
- 111040097
- Publisher
- John Wiley and Sons
- Year
- 2009
- Tongue
- English
- Weight
- 773 KB
- Volume
- 30
- Category
- Article
- ISSN
- 0143-9782
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This paper derives the asymptotic distribution of a class of M -estimators in a family of non-linear regression models when the errors and the design variables are long memory moving averages. The class of estimators includes analogs of the least square, least absolute deviation and the Huber(c) est