Light tails: all summands are large when the empirical mean is large
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Publication:488099
DOI10.1007/S10687-014-0187-8zbMath1306.60059OpenAlexW2062815827MaRDI QIDQ488099
Zhansheng Cao, Michel Broniatowski
Publication date: 23 January 2015
Published in: Extremes (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/s10687-014-0187-8
extreme valuesErdős-Rényi lawrandom walkconditional limit theoremlight tailsaggregate formingextreme deviation
Extreme value theory; extremal stochastic processes (60G70) Sums of independent random variables; random walks (60G50) Large deviations (60F10)
Related Items (2)
A Gibbs Conditional Theorem under Extreme Deviation ⋮ Refined behaviour of a conditioned random walk in the large deviations regime
Cites Work
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- Sanov property, generalized I-projection and a conditional limit theorem
- Conditional limit theorems for exponential families and finite versions of de Finetti's theorem
- An extended version of the Erdős-Rényi strong law of large numbers
- Blowing number of a distribution for a statistics and loyal estimators
- Tauberian theorems, Chernoff inequality and the tail behavior of finite convolutions of distribution functions
- Refinements of the Gibbs conditioning principle
- Critical phenomena in natural sciences. Chaos, fractals, selforganization and disorder: Concepts and tools.
- Densities with Gaussian Tails
- On a strong Tauberian result
- A Sharp Abelian Theorem for the Laplace Transform
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