In this article, we introduce a new generalization of Kavya-Manoharan Burr X (KMBx) distribution called exponentiated KMBx (EKMBx) distribution. The EKMBx distribution has three parameters, one scale and two shapes. These parameters make it very flexible. The EKMBx distribution contains three sub-models. Some basic statistical features like; the quantile function, skewness, kurtosis, moments, incomplete moments and generating functions are derived. The maximum likelihood approach is employed to estimate the parameters of the EKMBx model. The flexibility and applicability of the EKMBx model are demonstrated utilizing two different real-world datasets related to medical science.

Kavya-Manoharan Burr X distribution, exponentiated family, moments, maximum likelihood, skewness, kurtosis.

Received: March 12, 2023; Accepted: April 24, 2023; Published: June 8, 2023

How to cite this article: Ibrahim Elbatal, Safar M. Alghamdi, Anis BEN Ghorbal, A. W. Shawki, Mohammed Elgarhy and Ahmed R. El-Saeed, Exponentiated Kavya-Manoharan Burr X distribution: estimation under censored type II with applications in medical data, JP Journal of Biostatistics 23(3) (2023), 227-247. http://dx.doi.org/10.17654/0973514323013

This Open Access Article is Licensed under Creative Commons Attribution 4.0 International License

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