Local Linear Principle Component Regression Function Estimation.

• Main Authors: Ming-Horng Lin, 林銘宏
• Other Authors: Chu, C.K.
• Format: Others
• Language: zh-TW
• Published: 1999
• Online Access: http://ndltd.ncl.edu.tw/handle/05669606629232786924

碩士 === 國立東華大學 === 應用數學系 === 87 === In the case of the random design nonparametric regression, the local linear estimator（LLE）is the most popular kernel regression function estimator. However, there is a drawback to the LLE. That is, in some cases , the associated inverse matrix to the LLE may not exist. For exam- ple, there is only one design point falling in the compact window around the point at which the regression function value is estimated. To correct for the drawback to the LLE, we apply the idea of principle component analysis to the LLE, and propose the local linear principle component re-gression function estimator (LLPCRFE). Simulation studies demonstrate that the LLPCRFE has better performance than the ordinary LLE.