On optimal number of lags in variogram estimation in spatial data analysis

• 발행기관: 한국자료분석학회
• 저자명: Changkon Hong Younghwa Kim
• 간행물 정보: 『Journal of The Korean Data Analysis Society (JKDAS)』Vol.6 No.1, 39~70쪽, 전체 32쪽
• 주제분류: 자연과학 > 통계학
• 파일형태: PDF
• 발행일자: 2004.02.28

영문 초록

In the analysis of spatial data, the variogram plays an important role. Nonparametric estimator of the variogram is severely influenced by the number of lags, say K , which plays the role of a smoothing parameter. This means that K could cause a severe influence on both Least squares estimator and the kriging predictor. Therefore, it is very important to choose the proper value of K but few theoretical studies have been done on the choice of K. In applications, K is now being quite subjectively chosen. In this paper we have shown that under infill asymptotics very small value (1 or 2) of K gives best result even for very large number of sample size. The optimal order of K under mixed-increasing domain asymptotics is also obtained. The data-driven choice of K using cross-validation criterion is considered and the performance of this selection procedure is checked through simulation under several variogram models.

목차

1. Introduction

2. Nonparametric Variogram Estimator

3. Least Squares Estimation of the Variogram

4. Data Driven Choice of K Using Cross-validation Criterion

5. Concluding Remarks

References

키워드

Spatial data Variogram Kriging Number of lags Infill asymptotics