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Approximate maximum product spacing estimation of exponential distribution under multiply progressive censoring
Journal of the Korean Data & Information Science Society 2019;30:1197-205
Published online September 30, 2019;  https://doi.org/10.7465/jkdi.2019.30.5.1197
© 2019 Korean Data and Information Science Society.

Hyejin Shin1 · Kyeongjun Lee2

12Division of Mathematics and Big Data Science, Daegu University
Correspondence to: Associate professor, Division of Mathematics and Big Data Science, Daegu University, Gyeongsan 38453, Korea. E-mail: indra_74@naver.comindra_74@naver.com

This work was supported by Daegu University Undergraduate Research Program, 2019.
Received August 29, 2019; Revised September 11, 2019; Accepted September 11, 2019.
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
Abstract
There are many situation in life testing experiments in which units are lost or removed from experimentation before failure. In this paper, we propose the estimators of the parameter and reliability function of the ED under MPC scheme. First, we derive the MLE and MPSE for the parameter and reliability function of ED. And we derive the approximate MPSE for the parameter and reliability function of ED using Talyor series expansion. We also compare the proposed estimators in the sense of the root mean squared error (RMSE) and bias under MPC scheme. Finally, the validity of the proposed methods are demonstrated by a real data.
Keywords : Approximate MPSE, exponential distribuiton, multiply progressive censoring, Taylor series expansion.