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Portrait of Krzysztof Podgórski. Photo.

Krzysztof Podgórski

Professor, Head of the Department of Statistics

Portrait of Krzysztof Podgórski. Photo.

Sample Path Asymmetries in Non-Gaussian Random Processes

Author

  • Anastassia Baxevani
  • Krzysztof Podgorski
  • Jörg Wegener

Summary, in English

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.

Department/s

  • Department of Statistics
  • Mathematical Statistics

Publishing year

2014

Language

English

Pages

1102-1123

Publication/Series

Scandinavian Journal of Statistics

Volume

41

Issue

4

Document type

Journal article

Publisher

Wiley-Blackwell

Topic

  • Probability Theory and Statistics

Keywords

  • Laplace distribution
  • Matern covariance
  • moving average processes
  • Rice
  • formula
  • stationary second-order processes
  • tilting
  • time
  • irreversibility

Status

Published

ISBN/ISSN/Other

  • ISSN: 1467-9469