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The fundamentals of heavy tailsproperties, emergence, and estimation /

Record Type:	Electronic resources : Monograph/item
Title/Author:	The fundamentals of heavy tailsJayakrishnan Nair, Adam Wierman, Bert Zwart.
Reminder of title:	properties, emergence, and estimation /
Author:	Nair, Jayakrishnan.
other author:	Wierman, Adam.
Published:	Cambridge :Cambridge University Press,2022.
Description:	xiv, 250 p. :ill., digital ;26 cm.
Notes:	Title from publisher's bibliographic system (viewed on 07 Apr 2022).
Subject:	Distribution (Probability theory)Mathematical models.
Online resource:	https://doi.org/10.1017/9781009053730
ISBN:	9781009053730$q(electronic bk.)

The fundamentals of heavy tailsproperties, emergence, and estimation /
Nair, Jayakrishnan.

The fundamentals of heavy tailsproperties, emergence, and estimation /[electronic resource] :Jayakrishnan Nair, Adam Wierman, Bert Zwart. - Cambridge :Cambridge University Press,2022. - xiv, 250 p. :ill., digital ;26 cm. - Cambridge series in statistical and probabilistic mathematics ;53. - Cambridge series in statistical and probabilistic mathematics ;45..

Title from publisher's bibliographic system (viewed on 07 Apr 2022).

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.

ISBN: 9781009053730$q(electronic bk.)Subjects--Topical Terms:

280852
Distribution (Probability theory)
--Mathematical models.

LC Class. No.: QA273.6 / .N35 2022

Dewey Class. No.: 519.24

The fundamentals of heavy tailsproperties, emergence, and estimation /
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245 1 4 $a The fundamentals of heavy tails $h [electronic resource] : $b properties, emergence, and estimation / $c Jayakrishnan Nair, Adam Wierman, Bert Zwart.
260 $a Cambridge : $b Cambridge University Press, $c 2022.
300 $a xiv, 250 p. : $b ill., digital ; $c 26 cm.
490 1 $a Cambridge series in statistical and probabilistic mathematics ; $v 53
500 $a Title from publisher's bibliographic system (viewed on 07 Apr 2022).
520 $a 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.
650 0 $a Distribution (Probability theory) $x Mathematical models. $3 280852
700 1 $a Wierman, Adam. $3 930464
700 1 $a Zwart, Bert. $3 930465
830 0 $a Cambridge series in statistical and probabilistic mathematics ; $v 45. $3 796779
856 4 0 $u https://doi.org/10.1017/9781009053730