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Abstract
n this paper, we propose a new distribution, namely alpha-beta-skew generalized t
distribution. The proposed distribution is really flxible and includes as special models some important distributions like Normal, t-student, Cauchy and etc as its marginal component distributions. It features a probability density function with up to three modes. The moment generating function as well as the main moments are provided. Inference is based on a usual maximum-likelihood estimation approach and a small Monte Carlo simulation is conducted for studying the asymptotic properties of the maximum-likelihood estimate. The usefulness of the new model is illustrated in a real data
distribution. The proposed distribution is really flxible and includes as special models some important distributions like Normal, t-student, Cauchy and etc as its marginal component distributions. It features a probability density function with up to three modes. The moment generating function as well as the main moments are provided. Inference is based on a usual maximum-likelihood estimation approach and a small Monte Carlo simulation is conducted for studying the asymptotic properties of the maximum-likelihood estimate. The usefulness of the new model is illustrated in a real data
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How to Cite
Lak, F., Alizadeh, M., Monfared, M. E. D., & Esmaeili, H. (2019). The Alpha-Beta Skew Generalized t Distribution: Properties and Applications. Pakistan Journal of Statistics and Operation Research, 15(3), 605-616. https://doi.org/10.18187/pjsor.v15i3.2404
