Publication: Mod-Gaussian convergence and Its applications for models of statistical mechanics
Mod-Gaussian convergence and Its applications for models of statistical mechanics
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Méliot, P.-L., & Nikeghbali, A. (2015). Mod-Gaussian convergence and Its applications for models of statistical mechanics. In C. Donati-Martin, A. Lejay, & A. Rouault (Eds.), In Memoriam Marc Yor - Séminaire de Probabilités XLVII (No. 2137; Vol. 2137, pp. 369–425). Springer. https://doi.org/10.1007/978-3-319-18585-9_17
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In this paper we complete our understanding of the role played by the limiting (or residue) function in the context of mod-Gaussian convergence. The question about the probabilistic interpretation of such functions was initially raised by Marc Yor. After recalling our recent result which interprets the limiting function as a measure of “breaking of symmetry” in the Gaussian approximation in the framework of general central limit theorems type results, we introduce the framework of L$^{1}$-mod-Gaussian convergence in which the residue
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Méliot, P.-L., & Nikeghbali, A. (2015). Mod-Gaussian convergence and Its applications for models of statistical mechanics. In C. Donati-Martin, A. Lejay, & A. Rouault (Eds.), In Memoriam Marc Yor - Séminaire de Probabilités XLVII (No. 2137; Vol. 2137, pp. 369–425). Springer. https://doi.org/10.1007/978-3-319-18585-9_17