Abstract
There is a growing need for flexible statistical distributions that can accurately model data defined on the unit interval. This paper introduces a new unit distribution, termed the unit Shiha distribution, which is derived from the original Shiha distribution through an inverse exponential transformation. The probability density function of the unit Shiha distribution is sufficiently flexible to model both left‐ and right‐skewed data, while its hazard rate function is capable of capturing various failure‐rate patterns, including increasing, bathtub‐shaped, and J‐shaped forms. Several statistical properties of the proposed distribution are investigated, including moments and related measures, the quantile function, entropy, and stress–strength reliability. Parameter estimation is carried out using the maximum likelihood method, and its performance is evaluated through a simulation study. The practical usefulness of the unit Shiha distribution is demonstrated using four real‐life data sets, and its performance is compared with several well‐known competing unit distributions. The comparative results indicate that the proposed model provides a competitive fit compared with the other models considered in this study.