What question did this study set out to answer?

The aim is to introduce and analyze the unit power Rayleigh distribution for effective modeling of bounded data.

May 16, 2026Results in Control and OptimizationOpen Access

On the two-parameter unit power Rayleigh distribution: Properties, inference and applications

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The aim is to introduce and analyze the unit power Rayleigh distribution for effective modeling of bounded data.
Derived key properties including probability density, hazard rate, and raw moments.
Applied parameter estimation using maximum likelihood, least squares, and simulation methods.
Demonstrated applicability through analyses of two real engineering reliability datasets.
UPRD shows superior fitting capabilities compared to related unit distributions for bounded data.
Parameter estimation methods yielded adequate and efficient estimates with low biases and errors.
Key theoretical properties were effectively derived and validated through simulation studies.

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Implication

This randomized trial investigates the unit power Rayleigh distribution's performance in modeling reliability data, indicating its superior fit for bounded datasets.

Cite This Study

Al-Olaimat et al. (2026) studied this question.

synapsesocial.com/papers/6a080a5aa487c87a6a40c3e0 https://doi.org/10.1016/j.rico.2026.100734

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Implication

This randomized trial investigates the unit power Rayleigh distribution's performance in modeling reliability data, indicating its superior fit for bounded datasets.

On the two-parameter unit power Rayleigh distribution: Properties, inference and applications

Key Points

Discussion

Implication

Cite This Study

On the two-parameter unit power Rayleigh distribution: Properties, inference and applications

Key Points

Discussion

Implication

Cite This Study

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