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Slashed generalized exponential distribution

Author

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  • Juan M. Astorga
  • Héctor W. Gómez
  • Heleno Bolfarine

Abstract

In this paper, we introduce an extension of the generalized exponential (GE) distribution, making it more robust against possible influential observations. The new model is defined as the quotient between a GE random variable and a beta-distributed random variable with one unknown parameter. The resulting distribution is a distribution with greater kurtosis than the GE distribution. Probability properties of the distribution such as moments and asymmetry and kurtosis are studied. Likewise, statistical properties are investigated using the method of moments and the maximum likelihood approach. Two real data analyses are reported illustrating better performance of the new model over the GE model.

Suggested Citation

  • Juan M. Astorga & Héctor W. Gómez & Heleno Bolfarine, 2017. "Slashed generalized exponential distribution," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 46(5), pages 2091-2102, March.
    • Handle: RePEc:taf:lstaxx:v:46:y:2017:i:5:p:2091-2102
    DOI: 10.1080/03610926.2015.1032426
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    Cited by:

    1. Neveka M. Olmos & Emilio Gómez-Déniz & Osvaldo Venegas, 2022. "The Heavy-Tailed Gleser Model: Properties, Estimation, and Applications," Mathematics, MDPI, vol. 10(23), pages 1-16, December.
    2. Talha Arslan, 2021. "An α -Monotone Generalized Log-Moyal Distribution with Applications to Environmental Data," Mathematics, MDPI, vol. 9(12), pages 1-18, June.

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