Work

Entropy-transformed teissier distribution: A modern statistical framework for engineering, pharmaceutical, and metrological applications

Year: 2025

Type: article

Abstract: Statistical methods are crucial for making informed decisions under uncertainty. This study introduces a new probability model designed to improve data analysis in engineering, pharmaceutical sciences, and metrology. Traditional models often struggle with complex data patterns, so we propose a statistical framework based on the flexible Teissier distribution. The model's key properties are explored, and parameter estimation is carried out using reliable statistical techniques, supported by simulation studies. Real-world data from engineering, pharmaceutical, and metrological applications are used to assess the model's accuracy. Statistical tests confirm its consistency and precision. The entropy-transformed Teissier distribution shows strong adaptability, making it a practical and effective choice compared to existing methods.

Source: Journal of Radiation Research and Applied Sciences

DOI: 10.1016/j.jrras.2025.101773

Authors: Tabassum Naz Sindhu, Mohamed A. Abd Elgawad, Anum Shafiq, Tahani A. Abushal

Institutions: Quaid-i-Azam University, Imam Mohammad ibn Saud Islamic University, VSB - Technical University of Ostrava, Umm al-Qura University

Language: English

Topic: Statistical Distribution Estimation and Applications

Subfield: Statistics and Probability

Field: Mathematics

Domain: Physical Sciences

Open Access status: gold

Estimated APC paid: $1,400

Funders: Deanship of Scientific Research, Imam Mohammed Ibn Saud Islamic University, Imam Mohammed Ibn Saud Islamic University, Al-Imam Muhammad Ibn Saud Islamic University