Slepian noise approach for gaussian and Laplace moving average processes
Author
Summary, in English
Slepian models are derived for a stochastic process observed at level crossings of a moving average driven by a gaussian or Laplace noise. In particular, a Slepian model for the noise – the Slepian noise – is developed. For Laplace moving average process a method of sampling from the Slepian noise is also obtained by a Gibbs sampler. This facilitates comparison of behavior at crossing of a level between a gaussian process and a non-gaussian one and allows to study a random processes sampled at crossings of a non-gaussian moving average process. In a numerical study based on the method it is observed that the behavior of a non-gaussian moving average process at high level crossings is fundamentally different from that for the gaussian case, which is in line with some recent theoretical results on the subject.
Department/s
Publishing year
2015
Language
English
Pages
665-695
Publication/Series
Extremes
Volume
18
Issue
4
Document type
Journal article
Publisher
Springer
Topic
- Probability Theory and Statistics
Keywords
- Rice formula Level crossings
- Generalized Laplace distribution
- Moving average process
- Extreme episodes
- Tilted Rayleigh distribution
- Generalized inverse gaussian distribution
Status
Published
ISBN/ISSN/Other
- ISSN: 1572-915X