Sample Path Asymmetries in Non-Gaussian Random Processes
(2014) In Scandinavian Journal of Statistics 41(4). p.1102-1123- Abstract
- We tackle an important although rarely addressed question of accounting for a variety of asymmetries frequently observed in stochastic temporal/spatial records. First, we review some measures intending to capture such asymmetries that have been introduced on various occasions in the past and then propose a family of measures that is motivated by Rice's formula for crossing level distributions of the slope. We utilize those asymmetry measures to demonstrate how a class of second-order models built on the skewed Laplace distributions can account for sample path asymmetries. It is shown that these models are capable of mimicking not only distributional skewness but also more complex geometrical asymmetries in the sample path such as tilting,... (More)
- We tackle an important although rarely addressed question of accounting for a variety of asymmetries frequently observed in stochastic temporal/spatial records. First, we review some measures intending to capture such asymmetries that have been introduced on various occasions in the past and then propose a family of measures that is motivated by Rice's formula for crossing level distributions of the slope. We utilize those asymmetry measures to demonstrate how a class of second-order models built on the skewed Laplace distributions can account for sample path asymmetries. It is shown that these models are capable of mimicking not only distributional skewness but also more complex geometrical asymmetries in the sample path such as tilting, front-back slope asymmetry and time irreversibility. Simple moment-based estimation techniques are briefly discussed to allow direct application to modelling and fitting actual records. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/4982973
- author
- Baxevani, Anastassia ; Podgorski, Krzysztof LU and Wegener, Jörg LU
- organization
- publishing date
- 2014
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- Laplace distribution, Matern covariance, moving average processes, Rice, formula, stationary second-order processes, tilting, time, irreversibility
- in
- Scandinavian Journal of Statistics
- volume
- 41
- issue
- 4
- pages
- 1102 - 1123
- publisher
- Wiley-Blackwell
- external identifiers
-
- wos:000344860800014
- scopus:84920363206
- ISSN
- 1467-9469
- DOI
- 10.1111/sjos.12086
- language
- English
- LU publication?
- yes
- id
- cab6c6b4-6073-4b6f-a405-a74b924e7221 (old id 4982973)
- date added to LUP
- 2016-04-01 10:56:00
- date last changed
- 2022-03-12 18:24:12
@article{cab6c6b4-6073-4b6f-a405-a74b924e7221,
abstract = {{We tackle an important although rarely addressed question of accounting for a variety of asymmetries frequently observed in stochastic temporal/spatial records. First, we review some measures intending to capture such asymmetries that have been introduced on various occasions in the past and then propose a family of measures that is motivated by Rice's formula for crossing level distributions of the slope. We utilize those asymmetry measures to demonstrate how a class of second-order models built on the skewed Laplace distributions can account for sample path asymmetries. It is shown that these models are capable of mimicking not only distributional skewness but also more complex geometrical asymmetries in the sample path such as tilting, front-back slope asymmetry and time irreversibility. Simple moment-based estimation techniques are briefly discussed to allow direct application to modelling and fitting actual records.}},
author = {{Baxevani, Anastassia and Podgorski, Krzysztof and Wegener, Jörg}},
issn = {{1467-9469}},
keywords = {{Laplace distribution; Matern covariance; moving average processes; Rice; formula; stationary second-order processes; tilting; time; irreversibility}},
language = {{eng}},
number = {{4}},
pages = {{1102--1123}},
publisher = {{Wiley-Blackwell}},
series = {{Scandinavian Journal of Statistics}},
title = {{Sample Path Asymmetries in Non-Gaussian Random Processes}},
url = {{http://dx.doi.org/10.1111/sjos.12086}},
doi = {{10.1111/sjos.12086}},
volume = {{41}},
year = {{2014}},
}