We consider likelihood based inference for the parameter of a skewnormal 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.
A note on the asymptotic distribution of the maximum likelihood estimator for the scalar Skew-normal distribution
CHIOGNA, MONICA
2005
Abstract
We consider likelihood based inference for the parameter of a skewnormal 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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