Inference for Generalized Inverted Exponential Distribution UnderProgressive Type-I Interval Censored Data

Authors

  • Rana Hasan Department of Mathematics,College of Science, University of Basrah, Basrah, Iraq
  • Riyadh R. Al-Mosawi Department of Mathematics,College of Computer Science and Mathematics, University of Thi-Qar, Nasiriyah, Iraq
  • Abdullah Abdul Qader Department of Mathematics,College of Science, University of Basrah, Basrah, Iraq

DOI:

https://doi.org/10.24996/ijs.2024.65.1.22

Keywords:

Generalized Inverted Exponential Distribution (GIED), Progressive type-I interval censored, Probability plot, Stochastic expectation- maximization (SEM), Expectation-maximization(EM)

Abstract

This article discusses the estimation methods for parameters of a generalized inverted exponential distribution with different estimation methods by using Progressive type-I interval censored data. In addition to conventional maximum likelihood estimation, the mid-point method, probability plot method and method of moments are suggested for parameter estimation. To get maximum likelihood estimates, we utilize the Newton-Raphson, expectation -maximization and stochastic expectation-maximization methods. Furthermore, the approximate confidence intervals for the parameters are obtained via the inverse of the observed information matrix. The Monte Carlo simulations are used to introduce numerical comparisons of the proposed estimators. In addition, we use the percentile bootstrapping technique that is used to calculate confidence intervals. The proposed methodology in a real-life using the survival times of guinea pigs inoculated with different doses of tubercle bacilli data are considered to offer the applicability of the suggested methods.

 

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Published

2024-01-30

Issue

Section

Mathematics

How to Cite

Inference for Generalized Inverted Exponential Distribution UnderProgressive Type-I Interval Censored Data. (2024). Iraqi Journal of Science, 65(1), 250-270. https://doi.org/10.24996/ijs.2024.65.1.22

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