Statistical Inference on Accelerated Odd Fréchet Half-Logistic Distribution under Progressive Type-II Adaptive Hybrid Censoring with Application to Dielectric Circuits Using Binomial Removals

Authors

  • Ehab M. Almetwally Faculty of Business Administration, Delta University for Science and Technology, Gamasa 11152, Egypt
  • Samirah Alzubaidi Department of Mathematics, Al-Qunfudah University College, Umm Al-Qura University, Mecca, Saudi Arabia
  • Taher Sobh Department of Mathematics, Faculty of Science, Zagazig University, Zagazig 44519, Egypt
  • Eslam Hossam Department of Mathematics, Faculty of Science, Capital University, Cairo, Egypt

DOI:

https://doi.org/10.19139/soic-2310-5070-3558

Keywords:

progressive-stress; progressive type-II adaptive hybrid censoring; maximum likelihood estimation; Bayes estimation simulation study.

Abstract

This research presents a statistical work, where the sample is under a progressive stress-accelerated life test (PSALT) generated from the odd Fréchet half-logistic distribution (OFHLD) under adaptive progressive type-II hybrid censored (AP-II-HC) samples. The cumulative exposure model is applied to generate incremental stress samples. Both classical and Bayesian methodologies are used to estimate the unknown parameters of the distribution. Furthermore, the reliability function of the OFHLD is also calculated. The Metropolis-Hastings( MH) algorithm is applied to generate samples from the distribution. Moreover, the asymptotic and bootstrap confidence intervals (CIs) are constructed. A real data set is analyzed to illustrate the methodologies suggested in this study. Finally, some intriguing conclusions are noted and associated with future work suggestions.

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Published

2026-06-07

How to Cite

Almetwally, E. M., Alzubaidi, S., Sobh, T., & Hossam, E. (2026). Statistical Inference on Accelerated Odd Fréchet Half-Logistic Distribution under Progressive Type-II Adaptive Hybrid Censoring with Application to Dielectric Circuits Using Binomial Removals. Statistics, Optimization & Information Computing, 16(1), 542–566. https://doi.org/10.19139/soic-2310-5070-3558

Issue

Vol. 16 No. 1 (2026)

Section

Research Articles

License

Copyright (c) 2026 Ehab M. Almetwally, Samirah Alzubaidi, Taher Sobh, Eslam Hossam

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