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Research Article | Open Access

A flexible hyperbolic secant-B family of distributions with applications to lifetime and stress-strength data

Aijaz Ahmad1Ahmed R. El-Saeed2Taha Radwan3( )Manzoor A. Khanday4Ahlam H. Tolba5( )
Lincoln University College, Petaling Jaya-47301, Selangor, Malaysia
Department of Mathematics and Statistics, Faculty of Science, Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh 11432, Saudi Arabia
Department of Management Information Systems, College of Business and Economics, Qassim University, Buraydah 51452, Saudi Arabia
Department of Mathematics, Lovely Professional University, Punjab, India
Department of Mathematics, Faculty of Science, Mansoura University, Mansoura 35516, Egypt
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Abstract

Despite the availability of continuous distributions, few utilize the modeling potential of trigonometric functions, and none are based on the hyperbolic secant function. To fill this gap, we introduce the hyperbolic Sec-B family of trigonometric distributions. As a specific application, we introduce an adapted half-power logistic distribution (HS-PHLD) that retains a simple two-parameter form while offering greater versatility, particularly in tail behavior and skewness. Our research comprehensively explores this, establishing its fundamental mathematical properties, providing series expansions for its functions, and using both non-Bayesian and Bayesian estimation techniques. Monte Carlo simulations are used to validate the effectiveness of these estimators. Practically speaking, the HS-PHLD outperforms well-established models on three real-world datasets from the engineering and survival domains.

CLC number: 62A86, 62D05, 62F12, 62F25, 62G07, 62L05, 62L10, 62L12

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AIMS Mathematics
Pages 16837-16886

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Cite this article:
Ahmad A, El-Saeed AR, Radwan T, et al. A flexible hyperbolic secant-B family of distributions with applications to lifetime and stress-strength data. AIMS Mathematics, 2026, 11(6): 16837-16886. https://doi.org/10.3934/math.2026691

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Received: 31 January 2026
Revised: 13 April 2026
Accepted: 13 May 2026
Published: 15 June 2026
©2026 the Author(s), licensee AIMS Press.

This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0)