An Application of the Generalized Cross Validation to the Fundamental Cardinal Spline Estimates

• 발행기관: 한국자료분석학회
• 저자명: Jaerin Cho
• 간행물 정보: 『Journal of The Korean Data Analysis Society (JKDAS)』Vol.11 No.4, 1761~1769쪽, 전체 9쪽
• 주제분류: 자연과학 > 통계학
• 파일형태: PDF
• 발행일자: 2009.08.30

영문 초록

Recently, it showed that the kernel type estimates based on the fundamental cardinal splines were asymptotically optimal for certain functional classes. In order to show it, the asymptotically optimal bandwidth which depend on the parameters of given functional class was introduced. However, in practice, the parameters are hardly ever exactly known. So, a practical and appropriate bandwidth should be driven from the data. In this paper we consider the generalized cross validation(GCV) criterion as a method for selecting a bandwidth. We provide the simple formula of GCV criterion in fundamental cardinal spline estimates. In addition, a numerical example is given for illustrating the usefulness of GCV criterion in fundamental cardinal spline estimates.

목차

1. Introduction

2. The model

3. Fundamental Cardinal Spline Estimates

4. The Generalized Cross Validation

5. Simulation study

6. Conclusion Remarks

References

키워드

Non-parametric estimation cardinal spline kernel spline estimators analytic functional classes