A study of the remedies for nonparametric regression in the presence of sparse and multicollinear design.
碩士 === 淡江大學 === 統計學系碩士班 === 94 === In the case of the random design nonparametric regression, local linear estimator are an attractive choice due to many asymptotic properties. For the local linear estimator, however, if the data is in the presence of sparse and multicollinear design, it has the pro...
Main Authors: | Tsung-Hung Tsai, 蔡宗洪 |
---|---|
Other Authors: | 鄧文舜 |
Format: | Others |
Language: | zh-TW |
Published: |
2006
|
Online Access: | http://ndltd.ncl.edu.tw/handle/77145552743273458896 |
Similar Items
-
Partial Robust M-Regression Estimator in the Presence of Multicollinearity and Vertical Outliers
by: Majid, M.N.A, et al.
Published: (2020) -
Multicollinearity and the Estimation of Regression Coefficients
by: Teed, John Charles
Published: (1978) -
Multicollinearity, autocorrelation, and ridge regression
by: Hsu, Jackie Jen-Chy
Published: (2010) -
On Some Test Statistics for Testing the Regression Coefficients in Presence of Multicollinearity: A Simulation Study
by: Sergio Perez-Melo, et al.
Published: (2020-03-01) -
Comparison of Least Squares, Ridge Regression and Principal Component Approaches in the Presence of Multicollinearity in Regression Analysis
by: Soner Çankaya, et al.
Published: (2019-08-01)