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A note on the asymptotic distribution of the maximum likelihood estimator for the scalar skew-normal distribution

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Abstract.

We consider likelihood based inference for the parameter of a skew-normal distribution. One of the problems shown by this model is the singularity of the Fisher information matrix when skewness is absent. We derive the rate of convergence to the asymptotic distribution of the maximum likelihood estimator and study an alternative parameterization which overcomes problems related to the singularity of the information matrix.

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  1. Department of Statistical Sciences, University of Padova, Via Cesare Battisti 241, 35121, Padova, Italy

    Monica Chiogna

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  1. Monica Chiogna
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Chiogna, M. A note on the asymptotic distribution of the maximum likelihood estimator for the scalar skew-normal distribution. JISS 14, 331–341 (2005). https://doi.org/10.1007/s10260-005-0117-7

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  • DOI: https://doi.org/10.1007/s10260-005-0117-7

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