On a Perturbed Normal Distribution with Application to Analyzing a Screened Data

• 발행기관: 한국자료분석학회
• 저자명: Hea-Jung Kim
• 간행물 정보: 『Journal of The Korean Data Analysis Society (JKDAS)』Vol.8 No.2, 469~482쪽, 전체 14쪽
• 주제분류: 자연과학 > 통계학
• 파일형태: PDF
• 발행일자: 2006.04.30

영문 초록

This paper deals with the screening situation where the samples are drawn from the conditional distribution of a truncated bivariate normal distribution. The initial screening variable is doubly truncated, but only the values of the other variable are observed following the screening. Some properties of this conditional distribution, named as the perturbed normal distribution, are studied. The relationship of the distribution to skew-normal distribution is also obtained. The screened samples that are uninformative about the correlation of the bivariate normal distribution may occur, even for large sample size. MCMC method is employed to eliminate the uncertainty and to estimate the correlation as well as the unscreened population parameters of the conditional distribution. Illustrative examples demonstrate the performance of the method.

목차

1. Introduction

2. The Perturbed Normal Distribution

3. Bayesian Estimation

4. Numerical Examples

5. Conclusions

References

키워드

Screened data Perturbed Normal distribution Unscreened population MCMC