Assessment of Local Influence in Multivariate Regression with Linear Constraints

• 발행기관: 한국자료분석학회
• 저자명: 김명근(Myung Geun Kim)
• 간행물 정보: 『Journal of The Korean Data Analysis Society (JKDAS)』Vol.8 No.3, 895~900쪽, 전체 6쪽
• 주제분류: 자연과학 > 통계학
• 파일형태: PDF
• 발행일자: 2006.06.30

영문 초록

A method of detecting outliers using local influence is suggested for multivariate regression with linear constraints. It allows assessment of simultaneous perturbation affecting all the data. We consider a perturbation scheme of case-weights. This perturbation scheme simultaneously perturbs all the cases. The direction vector associated with the largest curvature of the curve at the null point provides information about outliers that cause a great change in the likelihood displacement. Observations corresponding to the component of the direction vector associated with the largest curvature that has substantially larger absolute value than the others are potential outliers. A numerical example is provided for illustration.

목차

1. Introduction

2. Preliminaries

3. Local Influence Measure

4. Some Computations

5. A numerical example

References

키워드

Linear constraints local influence multivariate regression outliers