An Algorithm for Generating Tie-Free Progressive Type-II Censored Samples From Discrete Distributions

Hanan Haj Ahmad and M. M. M. Mansour

Journal of Mathematics, 2026, vol. 2026, 1-13

Abstract: Progressive Type-II right censoring in discrete lifetime models frequently experiences ties, complicating the straightforward application of tie-free likelihood functions, defined earlier in the literature. In many practical settings, failure times are observed on a discrete scale, such as cycle counts, shock counts, inspection intervals, or days until event occurrence, where integer-valued observations and repeated values arise naturally. This study presents an algorithm for generating progressively censored samples that are assuredly free of ties, even when the initial observations include repeated values. This algorithm works by adjusting the progressive sample size and modifying the withdrawal scheme. The algorithm is especially useful in discrete lifetime models in which ties are a natural consequence. As an illustration of its usefulness, the approach is used to analyze medical data based on the generalized Poisson distribution (GPD). The method ensures that real-world experiments in discrete reliability can apply theoretical findings.

Date: 2026
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Persistent link: https://EconPapers.repec.org/RePEc:hin:jjmath:3657078

DOI: 10.1155/jom/3657078

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