[Lois de probabilités résultant de lois normales réitérées]
On considère un échantillon aléatoire
We consider a random sample
Accepté le :
Publié le :
Souad El Otmani 1 ; Armand Maul 1
@article{CRMATH_2009__347_3-4_201_0, author = {Souad El Otmani and Armand Maul}, title = {Probability distributions arising from nested {Gaussians}}, journal = {Comptes Rendus. Math\'ematique}, pages = {201--204}, publisher = {Elsevier}, volume = {347}, number = {3-4}, year = {2009}, doi = {10.1016/j.crma.2009.01.009}, language = {en}, }
Souad El Otmani; Armand Maul. Probability distributions arising from nested Gaussians. Comptes Rendus. Mathématique, Volume 347 (2009) no. 3-4, pp. 201-204. doi : 10.1016/j.crma.2009.01.009. https://comptes-rendus.academie-sciences.fr/mathematique/articles/10.1016/j.crma.2009.01.009/
[1] S. Arora, R. Kannan, Learning mixtures of arbitrary Gaussians, in: Symposium on Theory of Computing (STOC), 2001
[2] S. Dasgupta, Learning mixtures of Gaussians, in: Proc. of Symposium on Foundations of Computer Science (FOCS), 1999
[3] Finite Mixture Distributions, Chapman and Hall, New York, 1981
[4] Finite Mixture Models, Wiley, New York, 2000
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