Laplace probability distributions and related stochastic processes
(2012) p.105-145- Abstract
- Skew Laplace distributions, which naturally arise in connection with random summation
and quantile regression settings, offer an attractive and flexible alternative to
the normal (Gaussian) distribution in a variety of settings where the assumptions of
symmetry and short tail are too restrictive. The growing popularity of the Laplacebased
models in recent years is due to their fundamental properties, which include a
sharp peak at the mode, heavier than Gaussian tails, existence of all moments, infinite
divisibility, and, most importantly, random stability and approximation of geometric
sums. Since the latter arise quite naturally, these distributions provide useful... (More) - Skew Laplace distributions, which naturally arise in connection with random summation
and quantile regression settings, offer an attractive and flexible alternative to
the normal (Gaussian) distribution in a variety of settings where the assumptions of
symmetry and short tail are too restrictive. The growing popularity of the Laplacebased
models in recent years is due to their fundamental properties, which include a
sharp peak at the mode, heavier than Gaussian tails, existence of all moments, infinite
divisibility, and, most importantly, random stability and approximation of geometric
sums. Since the latter arise quite naturally, these distributions provide useful models
in diverse areas, such as biology, economics, engineering, finance, geosciences,
and physics. We review fundamental properties of these models, which give insight
into their applicability in these areas, and discuss extensions to time series, stochastic
processes, and random fields. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/3049663
- author
- Kozubowski, Tomasz and Podgorski, Krzysztof LU
- organization
- publishing date
- 2012
- type
- Chapter in Book/Report/Conference proceeding
- publication status
- published
- subject
- keywords
- vertical and horizontal asymmetry., stationary second order processes, subordination, selfsimilarity, random summation, random stability, quantile regression, parameter estimation, non-Gaussian moving average process, Mittag-Leffler distribution, microarray data analysis, geometric infinite divisibility, Linnink distribution, L´evy process, Laplace distribution, Bessel function distribution, geometric stable distribution
- host publication
- Probability: Interpretation, Theory and Applications
- editor
- Shmaliy, Yuriy
- pages
- 105 - 145
- publisher
- Nova Science Publishers, Inc.
- external identifiers
-
- scopus:84895277901
- ISBN
- 978-1-62100-249-9
- language
- English
- LU publication?
- yes
- id
- 1c40a92e-67e1-4fcd-b911-598ced683469 (old id 3049663)
- date added to LUP
- 2016-04-04 11:37:29
- date last changed
- 2022-01-29 22:09:32
@inbook{1c40a92e-67e1-4fcd-b911-598ced683469,
abstract = {{Skew Laplace distributions, which naturally arise in connection with random summation<br/><br>
and quantile regression settings, offer an attractive and flexible alternative to<br/><br>
the normal (Gaussian) distribution in a variety of settings where the assumptions of<br/><br>
symmetry and short tail are too restrictive. The growing popularity of the Laplacebased<br/><br>
models in recent years is due to their fundamental properties, which include a<br/><br>
sharp peak at the mode, heavier than Gaussian tails, existence of all moments, infinite<br/><br>
divisibility, and, most importantly, random stability and approximation of geometric<br/><br>
sums. Since the latter arise quite naturally, these distributions provide useful models<br/><br>
in diverse areas, such as biology, economics, engineering, finance, geosciences,<br/><br>
and physics. We review fundamental properties of these models, which give insight<br/><br>
into their applicability in these areas, and discuss extensions to time series, stochastic<br/><br>
processes, and random fields.}},
author = {{Kozubowski, Tomasz and Podgorski, Krzysztof}},
booktitle = {{Probability: Interpretation, Theory and Applications}},
editor = {{Shmaliy, Yuriy}},
isbn = {{978-1-62100-249-9}},
keywords = {{vertical and horizontal asymmetry.; stationary second order processes; subordination; selfsimilarity; random summation; random stability; quantile regression; parameter estimation; non-Gaussian moving average process; Mittag-Leffler distribution; microarray data analysis; geometric infinite divisibility; Linnink distribution; L´evy process; Laplace distribution; Bessel function distribution; geometric stable distribution}},
language = {{eng}},
pages = {{105--145}},
publisher = {{Nova Science Publishers, Inc.}},
title = {{Laplace probability distributions and related stochastic processes}},
year = {{2012}},
}