| Author/Presenter |
Victoria Zinde-Walsh (McGill University) |
| Co-author |
Dongming Zhu (Beijing University) |
| Title |
Properties and Estimation of Asymmetric Exponential Power Distribution |
| Abstract |
The new Asymmetric Exponential Power Distribution (AEPD) class proposed in this paper generalizes the Skewed Exponential Power Distributions (SEPD) by introducing different decay rates of density in the left and right tails. Our parametrization provides an interpretable role for each parameter. We derive moments and moment-based measures: skewness, kurtosis, expected shortfall and demonstrate a maximum entropy property for the AEPD distributions. Consistency, asymptotic normality and efficiency of the maximum likelihood estimators over a large part of the parameter space are proved by overcoming problems created by non-smooth likelihood function; explicit analytical expressions of the asymptotic covariance matrix are given; for the SEPD class the results enlarge on the current literature. We give a convenient stochastic representation of the distribution; the Monte Carlo study illustrates theoretical results. |
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