Approximate Maximum Product Spacings Estimation for the Parameter of a Rayleigh Distribution under Doubly Hybrid Censoring

• 발행기관: 한국자료분석학회
• 저자명: Kyeongjun Lee
• 간행물 정보: 『Journal of The Korean Data Analysis Society (JKDAS)』Vol.21 No.3, 1121~1129쪽, 전체 9쪽
• 주제분류: 자연과학 > 통계학
• 파일형태: PDF
• 발행일자: 2019.06.30

영문 초록

In most of the life testing and reliability experiments, the experimenter is often, unable to observe life time of all items put on test and the data available to the experimenter is censored data. Especially, hybrid censoring scheme is a mixture of types I and II censoring. Maximum product spacings method is most suitable method, especially to those cases where one of the parameter have an unknown shifted origin. In this paper, we consider the maximum product spacings estimator of the scale parameter when the samples are doubly hybrid censored samples. However, maximum likelihood estimator cannot be obtained in a closed form. Therefore, the second is to consider the approximate maximum product spacings estimator of the scale parameter when the samples are doubly hybrid censored samples. The different estimators are compared by performing the Monte Carlo simulation is presented. Also, real data example based on doubly hybrid censoring have been also analysed.

목차

1. Introduction

2. Estimation

3. Numerical Experiment

4. Conclusion

키워드

approximate maximum product spacings estimator doubly hybrid censoring scheme maximum product spacings estimator Rayleigh distribution