원문정보
국제문화기술진흥원
International Journal of Advanced Culture Technology(IJACT)
Volume 10 Number 1
2022.03
pp.236-241
피인용수 : 0건 (자료제공 : 네이버학술정보)
초록
영어
We consider methods of estimating a binary regression function using a nonparametric kernel estimation when there is only one covariate. For this, the Nadaraya-Watson estimation method using single and double bandwidths are used. For choosing a proper smoothing amount, the cross-validation and plug-in methods are compared. In the real data analysis for case study, German credit data and heart disease data are used. We examine whether the nonparametric estimation for binary regression function is successful with the smoothing parameter using the above two approaches, and the performance is compared.
목차
Abstract
1. INTRODUCTION
2. NONPARAMETRIC FUNCTION ESTIMATION
2.1 Kernel Density Estimation
2.2 Binary Regression Function Estimation
2.3 Bandwidth Selection Method
3. DATA ANALYSIS
3.1 German Credit Data
3.2 Heart Disease Data
4. CONCLUDING REMARKS
REFERENCES
1. INTRODUCTION
2. NONPARAMETRIC FUNCTION ESTIMATION
2.1 Kernel Density Estimation
2.2 Binary Regression Function Estimation
2.3 Bandwidth Selection Method
3. DATA ANALYSIS
3.1 German Credit Data
3.2 Heart Disease Data
4. CONCLUDING REMARKS
REFERENCES
저자정보
참고문헌
자료제공 : 네이버학술정보