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Robust optimality of Gaussian noise stability

Elchanan Mossel, Joe Neeman (2015)

Journal of the European Mathematical Society

We prove that under the Gaussian measure, half-spaces are uniquely the most noise stable sets. We also prove a quantitative version of uniqueness, showing that a set which is almost optimally noise stable must be close to a half-space. This extends a theorem of Borell, who proved the same result but without uniqueness, and it also answers a question of Ledoux, who asked whether it was possible to prove Borell’s theorem using a direct semigroup argument. Our quantitative uniqueness result has various...

Robust Parametric Estimation of Branching Processes with a Random Number of Ancestors

Stoimenova, Vessela (2005)

Serdica Mathematical Journal

2000 Mathematics Subject Classification: 60J80.The paper deals with a robust parametric estimation in branching processes {Zt(n)} having a random number of ancestors Z0(n) as both n and t tend to infinity (and thus Z0(n) in some sense). The offspring distribution is considered to belong to a discrete analogue of the exponential family – the class of the power series offspring distributions. Robust estimators, based on one and several sample paths, are proposed and studied for all values of the offspring...

Rough paths via sewing Lemma

Laure Coutin (2012)

ESAIM: Probability and Statistics

We present the rough path theory introduced by Lyons, using the swewing lemma of Feyel and de Lapradelle.

Rozdělení t a mnohorozměrná geometrie

Vítězslav Línek (2019)

Pokroky matematiky, fyziky a astronomie

V článku odvozujeme hustotu t rozdělení s využitím n -rozměrné geometrie. Oproti obvyklejším metodám k tomu nepotřebujeme předpoklad normality, postačující je nezávislost mnohorozměrného rozdělení na směru. Kromě základů diferenciálního počtu použijeme k odvození jen vzorec pro povrch n -rozměrné koule. Tento přístup byl inspirován metodami R. A. Fishera.

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