Central Limit Theorem and exponential tail estimations in mixed (anisotropic) Lebesgue spaces
arXiv:1308.5606
Abstract
We study the Central Limit Theorem (CLT) in the so-called mixed (anisotropic) Lebesgue-Riesz spaces and tail behavior of normed sums of centered random independent variables (vectors) with values in these spaces.
References in corpus (5)
- Schlomilch and Bell Series for Bessel's Functions, with Probabilistic Applications
- Asymptotic exponential bounds for MLE deviation under minimal conditions via classical and generic chaining methods
- Support of Borelian Measures in Separable Banach Spaces
- CLT for continuous random processes under approximations terms
- Moment and tail estimates for martingales and martingale transform, with application to the martingale limit theorem in Banach spaces
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- Random processes and Central Limit Theorem in Besov spaces
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