Journal article

Bimodal normal distribution: Extensions and applications

E Gomez-Deniz, JM Sarabia, E Calderin-Ojeda

Journal of Computational and Applied Mathematics | ELSEVIER | Published : 2021

Abstract

In this paper, a new family of continuous random variables with non-necessarily symmetric densities is introduced. Its density function can incorporate unimodality and bimodality features. Special attention is paid to the normal distribution which is included as a particular case. Its density function is given in closed-form which allows to easily compute probabilities, moments and other related measures such as skewness and kurtosis coefficients. Also, a stochastic representation of the family that enables us to generate random variates of this model is also presented. This new family of distributions is applied to explain the incidence of Hodgkin's disease by age. Other applications includ..

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University of Melbourne Researchers

Grants

Awarded by Ministerio de Economia, Industria y Competitividad Agencia Estatal de Investigacion, Spain


Awarded by Ministerio de Ciencia e Innovacion, Spain


Funding Acknowledgements

The authors thank the Associate Editor and an anonymous referee for their constructive comments and suggestions, which have greatly helped them to improve the paper. EGD was partially funded by grant ECO2017-85577-P (Ministerio de Economia, Industria y Competitividad. Agencia Estatal de Investigacion, Spain) JMS was partially funded by grant PID2019-105986GB-C22 (Ministerio de Ciencia e Innovacion, Spain).