Krzysztof Podgórski
Prefekt Statistiska institutionen, Professor
Estimation for Stochastic Models Driven by Laplace Motion
Författare
Summary, in English
Laplace motion is a Levy process built upon Laplace distributions. Non Gaussian stochastic fields that are integrals with respect to this process are considered and methods for their model fitting are discussed. The proposed procedures allow for inference about the parameters of the underlying Laplace distributions. A fit of dependence structure is also addressed. The importance of a convenient parameterization that admits natural and consistent estimation for this class of models is emphasized. Several parameterizations are introduced and their advantages over one another discussed. The proposed estimation method targets the standard characteristics: mean, variance, skewness and kurtosis. Their sample equivalents are matched in the closest possible way as allowed by natural constraints within this class. A simulation study and an example of potential applications conclude the article.
Avdelning/ar
- Statistiska institutionen
- Matematisk statistik
- MERGE: ModElling the Regional and Global Earth system
Publiceringsår
2011
Språk
Engelska
Sidor
3281-3302
Publikation/Tidskrift/Serie
Communications in Statistics: Theory and Methods
Volym
40
Issue
18
Dokumenttyp
Artikel i tidskrift
Förlag
Marcel Dekker
Ämne
- Probability Theory and Statistics
Nyckelord
- Kurtosis
- Laplace distribution
- Method of moment estimation
- Moving
- averages
- Skewness
- Stochastic fields
Aktiv
Published
ISBN/ISSN/Övrigt
- ISSN: 0361-0926