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An extended approach for the generalized powered uniform distribution

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  • Carlos Rondero-Guerrero

    (Autonomous University of Hidalgo State)

  • Isidro González-Hernández

    (Autonomous University of Hidalgo State)

  • Carlos Soto-Campos

    (Autonomous University of Hidalgo State)

Abstract

A new uniform distribution model, generalized powered uniform distribution (GPUD), which is based on incorporating the parameter k into the probability density function (pdf) associated with the power of random variable values and includes a powered mean operator, is introduced in this paper. From this new model, the shape properties of the pdf as well as the higher-order moments, the moment generating function, the model that simulates the GPUD and other important statistics can be derived. This approach allows the generalization of the distribution presented by Jayakumar and Sankaran (2016) through the new $${ GPUD }_{ (J-S)}$$ GPUD ( J - S ) distribution. Two sets of real data related to COVID-19 and bladder cancer were tested to demonstrate the proposed model’s potential. The maximum likelihood method was used to calculate the parameter estimators by applying the maxLik package in R. The results showed that this new model is more flexible and useful than other comparable models.

Suggested Citation

  • Carlos Rondero-Guerrero & Isidro González-Hernández & Carlos Soto-Campos, 2025. "An extended approach for the generalized powered uniform distribution," Computational Statistics, Springer, vol. 40(6), pages 2907-2930, July.
    • Handle: RePEc:spr:compst:v:40:y:2025:i:6:d:10.1007_s00180-022-01296-3
    DOI: 10.1007/s00180-022-01296-3
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    References listed on IDEAS

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    1. Manisha & M. MASOOM ALI & JUNGSOO WOO, 2006. "Exponentiated Weibull distribution," Statistica, Department of Statistics, University of Bologna, vol. 66(2), pages 139-147.
    2. Mohammed K. Shakhatreh, 2018. "A new three-parameter extension of the log-logistic distribution with applications to survival data," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 47(21), pages 5205-5226, November.
    3. Sanku Dey & Vikas Kumar Sharma & Mhamed Mesfioui, 2017. "A New Extension of Weibull Distribution with Application to Lifetime Data," Annals of Data Science, Springer, vol. 4(1), pages 31-61, March.
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    1. David Fernando Muñoz & Verónica Andrea González-López & Jürgen Symanzik, 2025. "Editorial on the special issue on the V Latin American conference on statistical computing," Computational Statistics, Springer, vol. 40(6), pages 2849-2856, July.

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