On the modeling of small sample distributions with generalized Gaussian density in a maximum likelihood framework

@article{Meignen2006OnTM,
  title={On the modeling of small sample distributions with generalized Gaussian density in a maximum likelihood framework},
  author={Sylvain Meignen and Hubert Meignen},
  journal={IEEE Transactions on Image Processing},
  year={2006},
  volume={15},
  pages={1647-1652}
}
The modeling of sample distributions with generalized Gaussian density (GGD) has received a lot of interest. Most papers justify the existence of GGD parameters through the asymptotic behavior of some mathematical expressions (i.e., the sample is supposed to be large). In this paper, we show that the computation of GGD parameters on small samples is not the same as on larger ones. In a maximum likelihood framework, we exhibit a necessary and sufficient condition for the existence of the… CONTINUE READING
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