<abstract xmlns="http://www.w3.org/1999/xhtml"><p>This paper presents a comparison of most capable families of distributions for modelling asymmetry. Kum-normal, stable-symmetric normal family and two of the full families were chosen, where the quality of the fit, the flexibility and the amount of asymmetry parameters were factors used for comparison. The objective of this study was to generate data with increasing levels of asymmetry and to choose the best fit. The distributions were also compared in modelling two data sets of pollution of the drinking water in the El-Sharkia governorate in Egypt. Much of this paper is concerned with the distribution theory, exploring the properties of some new recent families of distributions and, where appropriate, extolling their virtues. Relatively, much of this paper is devoted to practical application.</p></abstract>

This paper presents a comparison of most capable families of distributions for modelling asymmetry. Kum-normal, stable-symmetric normal family and two of the full families were chosen, where the quality of the fit, the flexibility and the amount of asymmetry parameters were factors used for comparison. The objective of this study was to generate data with increasing levels of asymmetry and to choose the best fit. The distributions were also compared in modelling two data sets of pollution of the drinking water in the El-Sharkia governorate in Egypt. Much of this paper is concerned with the distribution theory, exploring the properties of some new recent families of distributions and, where appropriate, extolling their virtues. Relatively, much of this paper is devoted to practical application.

Modern Techniques in Data Analysis, with Application to the Water Pollution

Department of Mathematics, Faculty of Science

Department of Physics and Engineering Mathematics, Faculty of Engineering

Proceedings of the Latvian Academy of Sciences. Section B. Natural, Exact, and Applied Sciences.

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

{"article-title":"Modern Techniques in Data Analysis, with Application to the Water Pollution"}

This paper presents a comparison of most capable families of distributions for modelling asymmetry. Kum-normal, stable-symmetric normal family and two of the...

Modern Techniques in Data Analysis, with Application to the Water Pollution

Online veröffentlicht: 21. Juni 2018

Seitenbereich: 184 - 192

Eingereicht: 12. Okt. 2017

Akzeptiert: 09. Jan. 2018

DOI: https://doi.org/10.2478/prolas-2018-0005

Schlüsselwörter
mixture distribution, full family of distributions, data modelling, skewness, kurtosis, drinking-water quality

© 2018 Haroon M. Barakat et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Modern Techniques in Data Analysis, with Application to the Water Pollution

Online veröffentlicht: 21. Juni 2018

Seitenbereich: 184 - 192

Eingereicht: 12. Okt. 2017

Akzeptiert: 09. Jan. 2018

DOI: https://doi.org/10.2478/prolas-2018-0005

Schlüsselwörtermixture distribution, full family of distributions, data modelling, skewness, kurtosis, drinking-water quality

© 2018 Haroon M. Barakat et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Schlüsselwörter
mixture distribution, full family of distributions, data modelling, skewness, kurtosis, drinking-water quality