Modified Confidence Intervals by Moriguti-Bulmer s Method with Optimal Conditions in One-Factor Components-of-Variance Model

• 발행기관: 한국자료분석학회
• 저자명: 강관중(Kwan-Joong Kang)
• 간행물 정보: 『Journal of The Korean Data Analysis Society (JKDAS)』Vol.9 No.4, 1601~1613쪽, 전체 13쪽
• 주제분류: 자연과학 > 통계학
• 파일형태: PDF
• 발행일자: 2007.08.30

영문 초록

The confidence intervals for σ²_A are given in various forms by many authors in one-factor components-of-variance model y_ij =mu + A_i + e_ij. In this model, Graybill and Wang s(1980) confidence intervals by using Moriguti(1954)-Bulmer s(1957) method for σ²_A are given by an asymptotic confidence intervals. By the simulations results of this confidence coefficients are not fit exactly the given confidence coefficient 1-alpha. Thus, we would like to give one of the optimal conditions and we can find out the more improved confidence intervals by the optimal conditions for σ²_A for the given Graybill and Wang s(1980) confidence intervals by using Moriguti(1954)-Bulmer s(1957) method in one-factor components-of-variance model.

목차

1. Introduction

2. One-Factor Components-of-Variance Model

3. Modified Confidence Intervals

4. Simulation Results

References

키워드

Confidence intervals Modified confidence coefficient Modified confidence intervals Optimal confidence intervals One-factor components-of-variance model Variance component