{"id":25846,"date":"2026-09-28T08:09:54","date_gmt":"2026-09-28T08:09:54","guid":{"rendered":"https:\/\/scientificassociation.org\/?post_type=journal-paper&#038;p=25846"},"modified":"2026-09-28T08:09:54","modified_gmt":"2026-09-28T08:09:54","slug":"statistical-inference-and-reliability-evaluation-of-the-perks-distribution-under-unified-hybrid-censoring-applications-to-carbon-fiber-gauge-data","status":"publish","type":"journal-paper","link":"https:\/\/scientificassociation.org\/ar\/journal-paper\/statistical-inference-and-reliability-evaluation-of-the-perks-distribution-under-unified-hybrid-censoring-applications-to-carbon-fiber-gauge-data\/","title":{"rendered":"Statistical Inference and Reliability Evaluation of the Perks Distribution under Unified Hybrid Censoring: Applications to Carbon-Fiber Gauge Data"},"content":{"rendered":"<div class=\"padding_abstract justify ltr\">In this paper, we develop statistical inference procedures for the Perks distribution under the Unified Hybrid Censoring Scheme (UHCS). Parameter estimation is performed using several methods, including maximum likelihood estimation (MLE), maximum product of spacings (MPS), and Bayesian estimation via Markov Chain Monte Carlo (MCMC). We derive point and interval estimators and evaluate their performance through a detailed Monte Carlo simulation study. The practical applicability of the proposed methodologies is demonstrated using actual carbon-fiber gauge data. Comparative investigations using many alternative models demonstrate that the Perks distribution offers the most parsimonious fit to the data. The results offer key insights for reliability and risk analysis of long-life components under censored data, supporting decisions under failure uncertainty.<\/div>\n","protected":false},"featured_media":25859,"template":"","meta":{"_acf_changed":false},"journal-name":[218],"paper-tag":[232,278,269],"class_list":["post-25846","journal-paper","type-journal-paper","status-publish","has-post-thumbnail","hentry","journal-name-cjmss","paper-tag-issue-2","paper-tag-november-2026","paper-tag-volume-5"],"acf":[],"_links":{"self":[{"href":"https:\/\/scientificassociation.org\/ar\/wp-json\/wp\/v2\/journal-paper\/25846","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/scientificassociation.org\/ar\/wp-json\/wp\/v2\/journal-paper"}],"about":[{"href":"https:\/\/scientificassociation.org\/ar\/wp-json\/wp\/v2\/types\/journal-paper"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/scientificassociation.org\/ar\/wp-json\/wp\/v2\/media\/25859"}],"wp:attachment":[{"href":"https:\/\/scientificassociation.org\/ar\/wp-json\/wp\/v2\/media?parent=25846"}],"wp:term":[{"taxonomy":"journal-name","embeddable":true,"href":"https:\/\/scientificassociation.org\/ar\/wp-json\/wp\/v2\/journal-name?post=25846"},{"taxonomy":"paper-tag","embeddable":true,"href":"https:\/\/scientificassociation.org\/ar\/wp-json\/wp\/v2\/paper-tag?post=25846"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}