On Stein's Method for Infinitely Divisible Laws with Finite First Moment On Stein's Method for Infinitely Divisible Laws with Finite First Moment
SpringerBriefs in Probability and Mathematical Statistics

On Stein's Method for Infinitely Divisible Laws with Finite First Moment

    • $59.99
    • $59.99

Publisher Description

This book focuses on quantitative approximation results for weak limit theorems when the target limiting law is infinitely divisible with finite first moment. Two methods are presented and developed to obtain such quantitative results. At the root of these methods stands a Stein characterizing identity discussed in the third chapter and obtained thanks to a covariance representation of infinitely divisible distributions. The first method is based on characteristic functions and Stein type identities when the involved sequence of random variables is itself infinitely divisible with finite first moment. In particular, based on this technique, quantitative versions of compound Poisson approximation of infinitely divisible distributions are presented. The second method is a general Stein's method approach for univariate selfdecomposable laws with finite first moment. Chapter 6 is concerned with applications and provides general upper bounds to quantify the rate of convergence in classicalweak limit theorems for sums of independent random variables. This book is aimed at graduate students and researchers working in probability theory and mathematical statistics.

GENRE
Science & Nature
RELEASED
2019
24 April
LANGUAGE
EN
English
LENGTH
115
Pages
PUBLISHER
Springer International Publishing
SELLER
Springer Nature B.V.
SIZE
11.3
MB

Other Books in This Series

Non-Gaussian Selfsimilar Stochastic Processes Non-Gaussian Selfsimilar Stochastic Processes
2023
Analytic Theory of Itô-Stochastic Differential Equations with Non-smooth Coefficients Analytic Theory of Itô-Stochastic Differential Equations with Non-smooth Coefficients
2022
Concentration of Maxima and Fundamental Limits in High-Dimensional Testing and Inference Concentration of Maxima and Fundamental Limits in High-Dimensional Testing and Inference
2021
Asymptotic Properties of Permanental Sequences Asymptotic Properties of Permanental Sequences
2021
An Invitation to Statistics in Wasserstein Space An Invitation to Statistics in Wasserstein Space
2020
Zero-Sum Discrete-Time Markov Games with Unknown Disturbance Distribution Zero-Sum Discrete-Time Markov Games with Unknown Disturbance Distribution
2020