Application of Standard Gaussion Kernel Function on Kernel Estimators of the First Two Order Derivatives and Curvature of Probability Density Function
碩士 === 國立中央大學 === 數學研究所 === 98 === In this paper, we find that the standard Guassian kernel function can be applied easily to construct the asymptotic unbiasedness of kernel estimators of the first two order derivatives of probability density function. we also find the central limit theorems for the...
Main Authors: | Yao-Cheng Chuang, 莊耀程 |
---|---|
Other Authors: | Yu-Sheng Hsu |
Format: | Others |
Language: | zh-TW |
Published: |
2010
|
Online Access: | http://ndltd.ncl.edu.tw/handle/38211212978340093429 |
Similar Items
-
Kernel Estimations of Stable Probability Density Functions
by: Yi-Xuan Liao, et al.
Published: (2002) -
Kernel Estimators for Some Functionals of Symmetric Probability Density Functions
by: Ying-an Chen, et al.
Published: (2009) -
On Kernel Estimates of Probability Densities
by: Horng, Wann Jyi, et al.
Published: (1995) -
The Performance of Kernel Estimator in Estimating Probability Density Function and Moments
by: Yu-Ming Shin, et al.
Published: (1999) -
Kernel Density Based Probability Estimation for Data Classifiers
by: Chun-Chieh Yang, et al.
Published: (2019)