Inverse Prediction Using Empirical Likelihood Ratio

• 발행기관: 한국자료분석학회
• 저자명: 홍창곤(Changkon Hong) 정미영(Miyoung Jung)
• 간행물 정보: 『Journal of The Korean Data Analysis Society (JKDAS)』Vol.8 No.5, 1675~1686쪽, 전체 12쪽
• 주제분류: 자연과학 > 통계학
• 파일형태: PDF
• 발행일자: 2006.10.30

영문 초록

The (interval) prediction of ratio-type quantity needs special technique called Fieller s method. In regression analysis the F statistic based inverse prediction works only if the normality assumption on the error terms is valid. Without the normality assumption, a nonparametric method which does not need the distributional assumption will be preferred. The nonparametric construction of confidence region using empirical likelihood ratio was developed by Owen(1991). In the inverse prediction problem, we suggest a new profile empirical likelihood ratio statistic, which is simpler than but as efficient as the Owen s. We prove an asymptotic theorem on the suggested statistic and check the efficiency via simulation.

목차

1. Introduction

2. Empirical likelihood and confidence region

3. Inverse prediction using empirical likelihood ratio

4. Simulation studies

References

키워드

empirical likelihood ratio inverse prediction ratio-type estimate confidence interval