Tags
Language
Tags
March 2024
Su Mo Tu We Th Fr Sa
25 26 27 28 29 1 2
3 4 5 6 7 8 9
10 11 12 13 14 15 16
17 18 19 20 21 22 23
24 25 26 27 28 29 30
31 1 2 3 4 5 6

Stable Convergence and Stable Limit Theorems (repost)

Posted By: libr
Stable Convergence and Stable Limit Theorems (repost)

Stable Convergence and Stable Limit Theorems (Probability Theory and Stochastic Modelling, Book 74) by Erich Haeusler and Harald Luschgy
English | 2015 | ISBN: 3319183281 | 228 pages | PDF | 2,3 MB

The authors present a concise but complete exposition of the mathematical theory of stable convergence and give various applications in different areas of probability theory and mathematical statistics to illustrate the usefulness of this concept. Stable convergence holds in many limit theorems of probability theory and statistics – such as the classical central limit theorem – which are usually formulated in terms of convergence in distribution. Originated by Alfred Rényi, the notion of stable convergence is stronger than the classical weak convergence of probability measures. A variety of methods is described which can be used to establish this stronger stable convergence in many limit theorems which were originally formulated only in terms of weak convergence. Naturally, these stronger limit theorems have new and stronger consequences which should not be missed by neglecting the notion of stable convergence. The presentation will be accessible to researchers and advanced students at the master's level with a solid knowledge of measure theoretic probability.