- International Journal of Informatics and Applied Mathematics
- Vol: 4 Issue: 2
- Pareto Randomization of the Scaling Parameter for the Gaussian Distribution
Pareto Randomization of the Scaling Parameter for the Gaussian Distribution
Authors : Miguel FELGUEİRAS, Rui SANTOS, Joao Paulo MARTİNS
Pages : 43-52
Doi:10.53508/ijiam.1020679
View : 14 | Download : 2
Publication Date : 2021-12-31
Article Type : Research
Abstract :Gaussian distribution is a common choice when dealing with symmetric data. However, other alternatives must be considered in applications with high tail-weight. One option is the randomization of the scale parameter for the Gaussian distribution, enabling a more flexible model for the tails albeit maintaining symmetry. Although any positive random variable can be used as a random scale parameter, Pareto distribution is a suitable choice in order to increase variance and tail-weight. Therefore, the aim of this work is to study the Pareto randomization of the scale parameter for symmetric distributions, in particular for the Gaussian distribution. Estimation problem is tackled and a simulation study is discussed. Finally, an application concerning the directions chosen by ants after a stimulus is provided. The results reveal that the proposed methodology works well both on simulated and real data.Keywords : Pareto scale mixtures, heavy tail distributions, parameters estimation, ants direction