A Marshall–Olkin variant of exponential Pareto distribution is being introduced in this paper. Some of its statistical functions and numerical characteristics among others characteristics function, moment generalizing function, central moments of real order are derived in the computational series expansion form and various illustrative special cases are discussed. This density function is utilized to model a real data set of cancer stem cells patients. The new distribution provides a better fit than related distributions. The proposed distribution could find applications for instance in the physical and biological sciences, hydrology, medicine, meteorology and engineering.
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American Journal of Theoretical and Applied Statistics (Volume 6, Issue 5-1)
This article belongs to the Special Issue Statistical Distributions and Modeling in Applied Mathematics |
DOI | 10.11648/j.ajtas.s.2017060501.11 |
Page(s) | 1-7 |
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This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited. |
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Copyright © The Author(s), 2017. Published by Science Publishing Group |
Pareto Distribution-Cancer Stem Cells-Biological Sciences
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APA Style
Khairia El-Said El-Nadi, L. M. Fatehy, Nourhan Hamdy Ahmed. (2017). Marshall-Olkin Exponential Pareto Distribution with Application on Cancer Stem Cells. American Journal of Theoretical and Applied Statistics, 6(5-1), 1-7. https://doi.org/10.11648/j.ajtas.s.2017060501.11
ACS Style
Khairia El-Said El-Nadi; L. M. Fatehy; Nourhan Hamdy Ahmed. Marshall-Olkin Exponential Pareto Distribution with Application on Cancer Stem Cells. Am. J. Theor. Appl. Stat. 2017, 6(5-1), 1-7. doi: 10.11648/j.ajtas.s.2017060501.11
@article{10.11648/j.ajtas.s.2017060501.11, author = {Khairia El-Said El-Nadi and L. M. Fatehy and Nourhan Hamdy Ahmed}, title = {Marshall-Olkin Exponential Pareto Distribution with Application on Cancer Stem Cells}, journal = {American Journal of Theoretical and Applied Statistics}, volume = {6}, number = {5-1}, pages = {1-7}, doi = {10.11648/j.ajtas.s.2017060501.11}, url = {https://doi.org/10.11648/j.ajtas.s.2017060501.11}, eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajtas.s.2017060501.11}, abstract = {A Marshall–Olkin variant of exponential Pareto distribution is being introduced in this paper. Some of its statistical functions and numerical characteristics among others characteristics function, moment generalizing function, central moments of real order are derived in the computational series expansion form and various illustrative special cases are discussed. This density function is utilized to model a real data set of cancer stem cells patients. The new distribution provides a better fit than related distributions. The proposed distribution could find applications for instance in the physical and biological sciences, hydrology, medicine, meteorology and engineering.}, year = {2017} }
TY - JOUR T1 - Marshall-Olkin Exponential Pareto Distribution with Application on Cancer Stem Cells AU - Khairia El-Said El-Nadi AU - L. M. Fatehy AU - Nourhan Hamdy Ahmed Y1 - 2017/01/24 PY - 2017 N1 - https://doi.org/10.11648/j.ajtas.s.2017060501.11 DO - 10.11648/j.ajtas.s.2017060501.11 T2 - American Journal of Theoretical and Applied Statistics JF - American Journal of Theoretical and Applied Statistics JO - American Journal of Theoretical and Applied Statistics SP - 1 EP - 7 PB - Science Publishing Group SN - 2326-9006 UR - https://doi.org/10.11648/j.ajtas.s.2017060501.11 AB - A Marshall–Olkin variant of exponential Pareto distribution is being introduced in this paper. Some of its statistical functions and numerical characteristics among others characteristics function, moment generalizing function, central moments of real order are derived in the computational series expansion form and various illustrative special cases are discussed. This density function is utilized to model a real data set of cancer stem cells patients. The new distribution provides a better fit than related distributions. The proposed distribution could find applications for instance in the physical and biological sciences, hydrology, medicine, meteorology and engineering. VL - 6 IS - 5-1 ER -