Modeling medical and engineering data using a new power function distribution: Theory and inference

Alshawarbeh, Etaf; Arshad, Muhammad Zeshan; Iqbal, Muhammad Zafar; Ghamkhar, Madiha; Al Mutairi, Aned; Meraou, Mohammed Amine; Hussam, Eslam; Alrashidi, Afaf

doi:10.1016/j.jrras.2023.100787

Cited by 2 publications

(2 citation statements)

References 31 publications

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“…Here, various estimation techniques for determining the APCos-ME's parameters are covered. For additional information concerning the application of estimation techniques, see Alshawarbeh et al [4], Rahman et al [18], Rodrigues et al [23], Shama et al [28], and Almetwally and Meraou [2]. 4.1.…”

Section: Estimation Methods Of Apcos-me Modelmentioning

confidence: 99%

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On the Analysis of Environmental and Engineering Data Using Alpha Power Transformed Cosine Moment Exponential Model

Alrweili

2024

Int. J. Anal. Appl.

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This article introduces a new model using the alpha power cosine transformed method for modeling complex data used in hydrology and engineering studies. The alpha power novel distribution transformed the cosine moment exponential model with two parameters. Its probability density function can be skewed and unimodal. Various statistical and mathematical properties are established, and the unknown parameters of the suggested model are determined using numerous estimation procedures. Also, the potential of these estimation techniques is calculated via some simulation studies. In the end, two real data sets are made using the proposed model to make a practical application in environmental and survival fields. The potential and utility of the recommended distribution are verified with other well known models and it shows great superiority in fitting the proposed data sets.

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Section: Estimation Methods Of Apcos-me Modelmentioning

confidence: 99%

“…The results are reported in Tables (2)-(4) represent the result. Tables(2)-(4) show that as the sample size increases, the AEs, ABs and MSEs decrease based on all estimation methods. This guarantees the consistency and asymptotic properties of all techniques.…”

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confidence: 99%

On the Analysis of Environmental and Engineering Data Using Alpha Power Transformed Cosine Moment Exponential Model

Alrweili

2024

Int. J. Anal. Appl.

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On bivariate compound exponentiated survival function of the beta distribution: estimation and prediction

Mahmoud,

Khashab,

Kalantan

et al. 2024

Journal of Radiation Research and Applied Sciences

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Modeling medical and engineering data using a new power function distribution: Theory and inference

Cited by 2 publications

References 31 publications

On the Analysis of Environmental and Engineering Data Using Alpha Power Transformed Cosine Moment Exponential Model

On the Analysis of Environmental and Engineering Data Using Alpha Power Transformed Cosine Moment Exponential Model

On bivariate compound exponentiated survival function of the beta distribution: estimation and prediction

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