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Open Access

ARTICLE

Analysis of Progressively Type-II Inverted Generalized Gamma Censored Data and Its Engineering Application

Refah Alotaibi1, Sanku Dey2, Ahmed Elshahhat3,*
1 Department of Mathematical Sciences, College of Science, Princess Nourah bint Abdulrahman University, P.O. Box 84428, Riyadh, 11671, Saudi Arabia
2 Department of Statistics, St. Anthony’s College, Shillong, 793001, India
3 Faculty of Technology and Development, Zagazig University, Zagazig, 44519, Egypt
* Corresponding Author: Ahmed Elshahhat. Email: email
(This article belongs to the Special Issue: Incomplete Data Test, Analysis and Fusion Under Complex Environments)

Computer Modeling in Engineering & Sciences https://doi.org/10.32604/cmes.2024.053255

Received 12 February 2024; Accepted 20 June 2024; Published online 19 July 2024

Abstract

A novel inverted generalized gamma (IGG) distribution, proposed for data modelling with an upside-down bathtub hazard rate, is considered. In many real-world practical situations, when a researcher wants to conduct a comparative study of the life testing of items based on cost and duration of testing, censoring strategies are frequently used. From this point of view, in the presence of censored data compiled from the most well-known progressively Type-II censoring technique, this study examines different parameters of the IGG distribution. From a classical point of view, the likelihood and product of spacing estimation methods are considered. Observed Fisher information and the delta method are used to obtain the approximate confidence intervals for any unknown parametric function of the suggested model. In the Bayesian paradigm, the same traditional inferential approaches are used to estimate all unknown subjects. Markov-Chain with Monte-Carlo steps are considered to approximate all Bayes’ findings. Extensive numerical comparisons are presented to examine the performance of the proposed methodologies using various criteria of accuracy. Further, using several optimality criteria, the optimum progressive censoring design is suggested. To highlight how the proposed estimators can be used in practice and to verify the flexibility of the proposed model, we analyze the failure times of twenty mechanical components of a diesel engine.

Keywords

Inverted generalized gamma; censoring; spacing function; likelihood; Bayesian; optimal plan

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