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Статті в журналах з теми "Variables aléatoires corrélées"
De Keizer, J., J. Paul, M. Albouy, A. Dupuis, V. Migeot, S. Rabouan, N. Venisse, and E. Gand. "Simulation et imputation de plusieurs variables corrélées dans un contexte de données manquantes de façon non aléatoires (MNAR)." Revue d'Épidémiologie et de Santé Publique 69 (June 2021): S32—S33. http://dx.doi.org/10.1016/j.respe.2021.04.052.
Повний текст джерелаShi, Jiamin, Rui Fu, Hayley Hamilton, and Michael Chaiton. "Une approche d’apprentissage automatique pour prédire l’utilisation des cigarettes électroniques et la dépendance à celles-ci chez les jeunes de l’Ontario." Promotion de la santé et prévention des maladies chroniques au Canada 42, no. 1 (January 2022): 23–31. http://dx.doi.org/10.24095/hpcdp.42.1.04f.
Повний текст джерелаMoussouni, Abdellatif, and Ammaria Metri. "Etude anthropo-sociologique des mariages consanguins dans la population de sabra (ouest-Algérien)." Lebanese Science Journal 20, no. 2 (August 27, 2019): 323–41. http://dx.doi.org/10.22453/lsj-020.2.323-341.
Повний текст джерелаДисертації з теми "Variables aléatoires corrélées"
Perret, Anthony. "Statistique d’extrêmes de variables aléatoires fortement corrélées." Thesis, Paris 11, 2015. http://www.theses.fr/2015PA112110/document.
Повний текст джерелаExtreme value statistics plays a keyrole in various scientific contexts. Although the description of the statistics of a global extremum is certainly an important feature, it focuses on the fluctuations of a single variable among many others. A natural question that arises is then the following: is this extreme value lonely at the top or, on the contrary, are there many other variables close to it ? A natural and useful quantity to characterize the crowding is the density of states near extremes. For this quantity, there exist very few exact results for strongly correlated variables, which is however the case encountered in many situations. Two physical models of strongly correlated variables have attracted much attention because they can be studied analytically : the positions of a random walker and the eigenvalues of a random matrix. This thesis is devoted to the study of the statistics near the maximum of these two ensembles of strongly correlated variables. In the first part, I study the case where the collection of random variables is the position of a Brownian motion, which may be constrained to be periodic or positive. This Brownian motion is seen as the limit of a classical random walker after a large number of steps. It is then possible to interpret this problem as a quantum particle in a potential which allows us to use powerful methods from quantum mechanics as propagators and path integral. These tools are used to calculate the average density from the maximum for different constrained Brownian motions and the complete distribution of this observable in certain cases. It is also possible to generalize this approach to the study of several random walks, independent or with interaction, as well as to the study of other functional of the maximum. In the second part, I study the case of the eigenvalues of random matrices, belonging to both Gaussian and Wishart ensembles. The study near the maximal eigenvalues for both models is performed using a method based on semi-classical orthogonal polynomials. In the case of Gaussian unitary matrices, I have obtained an analytical formula for the density near the maximum as well as a new expression for the distribution of the gap between the two largest eigenvalues. These results, and in particular their generalizations to different Gaussian ensembles, are then applied to the relaxational dynamics of a mean-field spin glass model. Finally, for the case of Wishart matrices I proposed a new derivation of the distribution of the smallest eigenvalue using orthogonal polynomials. In addition, I proved a conjecture on the first finite size correction of this distribution in the «hard edge» limit
Частини книг з теми "Variables aléatoires corrélées"
"Production de variables aléatoires corrélées." In Hasard, nombres aléatoires et méthode Monte Carlo, 73–90. Presses de l'Université du Québec, 2001. http://dx.doi.org/10.2307/j.ctv18ph276.7.
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