On Stein S Method For Infinitely Divisible Laws With Finite First Moment
Download On Stein S Method For Infinitely Divisible Laws With Finite First Moment PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get On Stein S Method For Infinitely Divisible Laws With Finite First Moment book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages.
On Stein's Method for Infinitely Divisible Laws with Finite First Moment
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.
High Dimensional Probability IX
This volume collects selected papers from the Ninth High Dimensional Probability Conference, held virtually from June 15-19, 2020. These papers cover a wide range of topics and demonstrate how high-dimensional probability remains an active area of research with applications across many mathematical disciplines. Chapters are organized around four general topics: inequalities and convexity; limit theorems; stochastic processes; and high-dimensional statistics. High Dimensional Probability IX will be a valuable resource for researchers in this area.
Recent Advances in Econometrics and Statistics
This volume presents a unique collection of original research contributions by leading experts in several modern fields of econometrics and statistics, including high-dimensional, nonparametric and robust statistics, time series analysis and factor models. Published in honour of Marc Hallin on the occasion of his 75th birthday, it puts emphasis on the fundamental and applied topics he has significantly contributed to. The volume starts with an annotated bibliography that mainly catalogues his contributions to distribution-free rank-based and quantile-oriented inference and to time series analysis. The main part of the book collects 29 authoritative contributions by some of Marc Hallin’s main collaborators, organized into six parts: rank- and depth-based methods, asymptotic statistics, quantile regression, econometrics, statistical modelling and related topics, and high-dimensional and non-Euclidean data.