Extended Gamma Distribution to Fitting Breast Tumors

Adel Abbood Najm ; Bashar Khalid Ali
International Journal of Applied Mathematics and C... 📅 2025 Vol 2, No 1 🔗 DOI: 10.62951/ijamc.v2i1.109
Abstract
There are many patterns of breast cancer change that make it a global health challenge. The research aims to propose an expanded gamma distribution with parameters and apply it to data for (103) patients with breast cancer. Data normality tests were used, such as the Kolmigrov-Smirnov test, the Anderson-Darling test, and the Chi-square test, to fit the real data. The parameters of the proposed distribution were estimated using the maximum likelihood method. It was found that there is a large difference in the real data with positive Skewness in it. The maximum likelihood estimates reflected the suitability of the data to the proposed distribution, which indicates the accuracy of the obtained results.
Keywords
Breast Cancer; Distribution; Normality; Skewness
How to Cite

Adel Abbood Najm & Bashar Khalid Ali (2025). Extended Gamma Distribution to Fitting Breast Tumors. International Journal of Applied Mathematics and Computing, 2(1). https://doi.org/10.62951/ijamc.v2i1.109

Adel Abbood Najm; Bashar Khalid Ali, "Extended Gamma Distribution to Fitting Breast Tumors," International Journal of Applied Mathematics and Computing, vol. 2, no. 1, 2025.

Adel Abbood Najm; Bashar Khalid Ali. "Extended Gamma Distribution to Fitting Breast Tumors." International Journal of Applied Mathematics and Computing, vol. 2, no. 1, 2025.

Adel Abbood Najm; Bashar Khalid Ali. "Extended Gamma Distribution to Fitting Breast Tumors." International Journal of Applied Mathematics and Computing 2, no. 1 (2025).

Adel Abbood Najm & Bashar Khalid Ali (2025) 'Extended Gamma Distribution to Fitting Breast Tumors', International Journal of Applied Mathematics and Computing, 2(1). doi: 10.62951/ijamc.v2i1.109.

Adel Abbood Najm; Bashar Khalid Ali. Extended Gamma Distribution to Fitting Breast Tumors. International Journal of Applied Mathematics and Computing. 2025;2(1).

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