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One-dimensional stable distributions
TLDR
In this article, the authors present examples of stable laws in applications, including analytical properties of the distributions in the family, special properties of laws in the class, and estimators of the parameters of stable distributions.Abstract:
Examples of stable laws in applications Analytic properties of the distributions in the family $\mathfrak S$ Special properties of laws in the class $\mathfrak W$ Estimators of the parameters of stable distributions.read more
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Book
Analytic Combinatorics
TL;DR: This text can be used as the basis for an advanced undergraduate or a graduate course on the subject, or for self-study, and is certain to become the definitive reference on the topic.
Journal ArticleDOI
Non-Uniform Random Variate Generation.
B. J. T. Morgan,Luc Devroye +1 more
TL;DR: This chapter reviews the main methods for generating random variables, vectors and processes in non-uniform random variate generation, and provides information on the expected time complexity of various algorithms before addressing modern topics such as indirectly specified distributions, random processes, and Markov chain methods.
Book
Non-uniform random variate generation
TL;DR: A survey of the main methods in non-uniform random variate generation can be found in this article, where the authors provide information on the expected time complexity of various algorithms, before addressing modern topics such as indirectly specified distributions, random processes and Markov chain methods.
Proceedings ArticleDOI
Locality-sensitive hashing scheme based on p-stable distributions
TL;DR: A novel Locality-Sensitive Hashing scheme for the Approximate Nearest Neighbor Problem under lp norm, based on p-stable distributions that improves the running time of the earlier algorithm and yields the first known provably efficient approximate NN algorithm for the case p<1.
Journal ArticleDOI
Modelling Extremal Events for Insurance and Finance
TL;DR: In this article, Modelling Extremal Events for Insurance and Finance is discussed. But the authors focus on the modeling of extreme events for insurance and finance, and do not consider the effects of cyber-attacks.