Nakagami Distribution with Heavy Tails and Applications to Mining Engineering Data
- Reyes, Jimmy - Rojas, Mario A. - Venegas, Osvaldo - Gomez, Hector W.
- Datos de publicación:
- JOURNAL OF STATISTICAL THEORY AND PRACTICE,Vol.14,,2020
- Kurtosis - Maximum likelihood estimator - Slash-Nakagami distribution
- Migración Web of Science 
- In this paper we introduce a new extension of the Nakagami distribution. This new distribution is obtained by the quotient of two independent random variables. The quotient consists of a Nakagami distribution divided by a power of the uniform distribution in (0,1). Thus the new distribution has a heavier tail than the Nakagami distribution. In this study we obtain the density function and some important properties for making the inference, such as estimators of moment and maximum likelihood. We examine two sets of real data from the mining industry which show the usefulness of the new model in analyses with high kurtosis.