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Limit Theorems of Probability Theory
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The present reprint contains all of the articles accepted and published in the Special Issue titled “Limit Theorems of Probability Theory”. The papers included in this Special Issue present new directions and advances for limit theorems in probability theory and its applications. The list of topics is extensive, and it includes classical models of sums of both independent and various types of dependent random variables; probabilities of large deviations; functional limit theorems and limit theorems for random processes, in high-dimensional spaces, for spectra of random matrices, and for random graphs, etc. We strongly believe that the selected topics and results will be attractive to and useful for the international scientific community, as well as contribute to further research into the subject of limit theorems in probability theory.
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Keywords
- asymptotic expansions for symmetric statistics
- asymptotic normality
- central limit theorem
- functional limit theorem
- Gaussian distribution
- law of iterated logarithms
- laws of large numbers
- limit distributions of extremes
- Mathematics & science
- measure concentration
- multivariate statistics
- point process
- Poisson limit distribution
- probabilities of large deviations
- probability theory
- Random matrices
- Reference, information & interdisciplinary subjects
- Research & information: general
- sequences of random variables
- sparse sample covariance matrices
- sums of random variables
Links
DOI: 10.3390/books978-3-0365-9193-3Editions