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Parameter estimation for univariate Skew-Normal distribution based on the modified empirical characteristic function

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posted on 2021-03-16, 03:50 authored by Gege Hou, Ancha Xu, Fengjing Cai, You-Gan Wang

Parameter estimation for the skew-normal distribution is challenging, since the profile likelihood function of shape parameter has a stationary point at zero, which hampers the use of traditional methods, such as maximum likelihood method. We present a modified empirical characteristic function method to perform parameter estimation for the skew-normal distribution. The proposed approach is flexible and easy to implement. We show that the estimators converge to the true values in probability. The simulation study and data analysis suggest that the proposed method performs well, even for the case of small sample size.

Funding

The research is supported by National Natural Science Foundation of China (11671303) and Foundation of Zhejiang Province(LY19A010014).

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