We show that a nonparametric estimator of a regression function, obtained as solution of a specific regularization problem is the best linear unbiased predictor in some nonparametric mixed effect model. Since this estimator is intractable from a numerical point of view, we propose a tight approximat
β¦ LIBER β¦
Wavelet estimation in nonparametric model under martingale difference errors
β Scribed by Hanying Liang; Dongxia Zhang; Baoxian Lu
- Publisher
- SP Editorial Committee of Applied Mathematics - A Journal of Chinese Universities
- Year
- 2004
- Tongue
- English
- Weight
- 363 KB
- Volume
- 19
- Category
- Article
- ISSN
- 1005-1031
No coin nor oath required. For personal study only.
π SIMILAR VOLUMES
Wavelet regression estimation in nonpara
β
Claudia Angelini; Daniela De Canditiis; FrΓ©dΓ©rique Leblanc
π
Article
π
2003
π
Elsevier Science
π
English
β 510 KB
Wavelet Estimation in Heteroscedastic Mo
β
Han Ying Liang; Jong Il Baek
π
Article
π
2007
π
Institute of Mathematics, Chinese Academy of Scien
π
English
β 240 KB
Nonparametric regression estimation in m
β
Ricardo Fraiman; Gonzalo PΓ©rez Iribarren
π
Article
π
1991
π
Elsevier Science
π
English
β 834 KB
Nonparametric estimation of varying coef
β
Yazhao Lv; Riquan Zhang; Zhensheng Huang
π
Article
π
2011
π
Elsevier Science
π
English
β 976 KB
Asymptotic normality of wavelet estimato
β
Hanying Liang
π
Article
π
2010
π
Academy of Mathematics and Systems Science, Chines
π
English
β 405 KB
Admissibility of the usual estimators un
β
Guohua Zou; Hua Liang
π
Article
π
1997
π
Elsevier Science
π
English
β 382 KB
In this paper, we first point out that a result in Mukhopadhyay (1994) on the optimality of the usual estimator s 2 of 2 (wherefmeans finite population variance is not true. We then give a necessary and sufficient condition for ((1 -f)/n) sy the sampling fraction) as the estimator of the precision o