The Laplace Distribution and Generalizations

The Laplace Distribution and Generalizations
Author: Samuel Kotz
Publisher: Springer Science & Business Media
Total Pages: 358
Release: 2012-12-06
Genre: Mathematics
ISBN: 146120173X

This book describes the inferential and modeling advantages that this distribution, together with its generalizations and modifications, offers. The exposition systematically unfolds with many examples, tables, illustrations, and exercises. A comprehensive index and extensive bibliography also make this book an ideal text for a senior undergraduate and graduate seminar on statistical distributions, or for a short half-term academic course in statistics, applied probability, and finance.

The Laplace Distribution and Generalizations

The Laplace Distribution and Generalizations
Author: Samuel Kotz
Publisher: Birkhäuser
Total Pages: 349
Release: 2001-05-18
Genre: Mathematics
ISBN: 9780817641665

This book describes the inferential and modeling advantages that this distribution, together with its generalizations and modifications, offers. The exposition systematically unfolds with many examples, tables, illustrations, and exercises. A comprehensive index and extensive bibliography also make this book an ideal text for a senior undergraduate and graduate seminar on statistical distributions, or for a short half-term academic course in statistics, applied probability, and finance.

A Multivariate and Asymmetric Generalization of Laplace Distribution

A Multivariate and Asymmetric Generalization of Laplace Distribution
Author: Tomasz J. Kozubowski
Publisher:
Total Pages: 0
Release: 2001
Genre:
ISBN:

Consider a sum of independent and identically distributed random vectors with finite second moments, where the number of terms has a geometric distribution independent of the summands. We show that the class of limiting distributions of such random sums, as the number of terms converges to infinity, consists of multivariate asymmetric distributions that are natural generalizations of univariate Laplace laws. We call these limits multivariate asymmetric Laplace laws. We give an explicit form of their multidimensional densities and show representations that effectively facilitate computer simulation of variates from this class. We also discuss the relation to other formerly considered classes of distributions containing Laplace laws.

Advances in Distribution Theory, Order Statistics, and Inference

Advances in Distribution Theory, Order Statistics, and Inference
Author: N. Balakrishnan
Publisher: Springer Science & Business Media
Total Pages: 552
Release: 2006-05-17
Genre: Mathematics
ISBN:

The purpose of this book is to honor the fundamental contributions to many different areas of statistics made by Barry Arnold. Distinguished and active researchers highlight some of the recent developments in statistical distribution theory, order statistics and their properties, as well as inferential methods associated with them. Applications to survival analysis, reliability, quality control, and environmental problems are emphasized.

L-Laplace Processes

L-Laplace Processes
Author: Lee S Dewald (Sr)
Publisher:
Total Pages: 33
Release: 1988
Genre:
ISBN:

A broad family of symmetric, thick tailed distributions, the small l-Laplace distributions, is described. These are natural generalizations of the Laplace distribution. A family of random coefficient Autoregressive Moving Average processes with small l-Laplace marginal distributions is constructed and its properties are explored. Extensions to ARIMA processes are considered. The first order autoregression with a standard Laplace marginal distribution is examined in detail and different estimates of the autoregressive parameter are compared theoretically and by simulation. Keywords: Random variables. (kr).

The Fundamentals of Heavy Tails

The Fundamentals of Heavy Tails
Author: Jayakrishnan Nair
Publisher: Cambridge University Press
Total Pages: 266
Release: 2022-06-09
Genre: Mathematics
ISBN: 1009062964

Heavy tails –extreme events or values more common than expected –emerge everywhere: the economy, natural events, and social and information networks are just a few examples. Yet after decades of progress, they are still treated as mysterious, surprising, and even controversial, primarily because the necessary mathematical models and statistical methods are not widely known. This book, for the first time, provides a rigorous introduction to heavy-tailed distributions accessible to anyone who knows elementary probability. It tackles and tames the zoo of terminology for models and properties, demystifying topics such as the generalized central limit theorem and regular variation. It tracks the natural emergence of heavy-tailed distributions from a wide variety of general processes, building intuition. And it reveals the controversy surrounding heavy tails to be the result of flawed statistics, then equips readers to identify and estimate with confidence. Over 100 exercises complete this engaging package.

A History of the Central Limit Theorem

A History of the Central Limit Theorem
Author: Hans Fischer
Publisher: Springer Science & Business Media
Total Pages: 415
Release: 2010-10-08
Genre: Mathematics
ISBN: 0387878572

This study discusses the history of the central limit theorem and related probabilistic limit theorems from about 1810 through 1950. In this context the book also describes the historical development of analytical probability theory and its tools, such as characteristic functions or moments. The central limit theorem was originally deduced by Laplace as a statement about approximations for the distributions of sums of independent random variables within the framework of classical probability, which focused upon specific problems and applications. Making this theorem an autonomous mathematical object was very important for the development of modern probability theory.

Distribution Theory

Distribution Theory
Author: Gerrit Dijk
Publisher: Walter de Gruyter
Total Pages: 120
Release: 2013-03-22
Genre: Mathematics
ISBN: 3110298511

The theory of distributions has numerous applications and is extensively used in mathematics, physics and engineering. There is however relatively little elementary expository literature on distribution theory. This book is intended as an introduction. Starting with the elementary theory of distributions, it proceeds to convolution products of distributions, Fourier and Laplace transforms, tempered distributions, summable distributions and applications. The theory is illustrated by several examples, mostly beginning with the case of the real line and then followed by examples in higher dimensions. This is a justified and practical approach, it helps the reader to become familiar with the subject. A moderate number of exercises are added. It is suitable for a one-semester course at the advanced undergraduate or beginning graduate level or for self-study.