@inproceedings{d2c8a80e9d0d42b08ad5a5f7ba70f47c,
title = "Parameter estimation of exponentiated exponential distribution for left censored data using Bayesian method",
abstract = "Exponentiated Exponential (EE) distribution is the development of Exponential Distribution by adding α as a shape parameter. This distribution can solve unflexibility issue in Exponential distribution. In order to make inferences about any cases modeled with EE distribution, parameter estimation is required. This paper will discuss about parameter estimation of Exponentiated Exponential distribution for left censored data using Bayesian method. Parameter estimation procedure are selection of prior distribution which is conjugate prior, likelihood construction for left censored data, and then forming posterior distribution. Bayes estimator can be obtained by minimize posterior risk based on Squared Error Loss Function (SELF) and Precautionary Loss Function (PLF). After Bayes estimator is obtained, simulation is done to compare the results of Bayes estimator using SELF and PLF which are seen from the result of Mean Square Error (MSE). Loss function is said to be more effective to obtain Bayes estimator if the resulting Bayes estimator yield smaller MSE. Based on simulation, PLF more effective for α ≤ 1, while SELF more effective for α > 1.",
keywords = "Bayesian method, Exponentiated Exponential, left censored data, loss function, posterior distribution, prior distribution",
author = "M. Margaretha and I. Fithriani and S. Abdullah",
note = "Funding Information: This research is funded by Hibah Publikasi Internasional Terindeks Tugas Akhir (Hibah PITTA B) from Universitas Indonesia, fiscal year 2019 with No: NKB-0665/UN2.R3.1/HKP.05.00/2019. Publisher Copyright: {\textcopyright} 2020 Author(s).; 5th International Symposium on Current Progress in Mathematics and Sciences, ISCPMS 2019 ; Conference date: 09-07-2019 Through 10-07-2019",
year = "2020",
month = jun,
day = "1",
doi = "10.1063/5.0007892",
language = "English",
series = "AIP Conference Proceedings",
publisher = "American Institute of Physics Inc.",
editor = "Terry Mart and Djoko Triyono and Ivandini, {Tribidasari Anggraningrum}",
booktitle = "Proceedings of the 5th International Symposium on Current Progress in Mathematics and Sciences, ISCPMS 2019",
}