Exponentially-Modified Logistic Distribution with Application to Mining and Nutrition Data

Authors

Jimmy Reyes, Departamento de Matem´aticas, Facultad de Ciencias B´asicas, Universidad de Antofagasta, Antofagasta, Chile.Follow
Osvaldo Venegas, Departamento de Ciencias Matem´aticas y F´ısicas, Facultad de Ingenier´ıa, Universidad Cat´olica de Temuco, ChileFollow
Hector W. Gomez, Departamento de Matem´aticas, Facultad de Ciencias B´asicas, Universidad de Antofagasta, Antofagasta, Chile.Follow

Author Country (or Countries)

Chile

Abstract

In this work we introduce a modification of the exponentially-modified Gaussian distribution. This new distribution is obtained by combining a logistic distribution with an exponential distribution, and is more flexible than other similar distributions. We provide a closed expression for the density function and obtain some important properties useful for making inferences, such as moment estimators and maximum likelihood estimators. By way of illustration, and using real data to show the effectiveness of the new model, we compare it with known related models, showing that the new model achieves a better fit.

Digital Object Identifier (DOI)

http://dx.doi.org/10.18576/amis/120605

Recommended Citation

Reyes, Jimmy; Venegas, Osvaldo; and W. Gomez, Hector (2018) "Exponentially-Modified Logistic Distribution with Application to Mining and Nutrition Data," Applied Mathematics & Information Sciences: Vol. 12: Iss. 6, Article 5.
DOI: http://dx.doi.org/10.18576/amis/120605
Available at: https://digitalcommons.aaru.edu.jo/amis/vol12/iss6/5