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Estimation for Stochastic Models Driven by Laplace Motion

Podgorski, Krzysztof LU and Wegener, Jörg LU (2011) In Communications in Statistics: Theory and Methods 40(18). p.3281-3302
Abstract
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... (More)
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. (Less)
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author
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
Kurtosis, Laplace distribution, Method of moment estimation, Moving, averages, Skewness, Stochastic fields
in
Communications in Statistics: Theory and Methods
volume
40
issue
18
pages
3281 - 3302
publisher
Marcel Dekker
external identifiers
  • wos:000294890500007
  • scopus:79960451666
ISSN
0361-0926
DOI
10.1080/03610926.2010.499051
project
MERGE
language
English
LU publication?
yes
id
3efdb095-51d2-4d66-92d1-7c1807e8c719 (old id 2187153)
date added to LUP
2011-10-24 11:59:10
date last changed
2017-01-01 05:44:43
@article{3efdb095-51d2-4d66-92d1-7c1807e8c719,
  abstract     = {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.},
  author       = {Podgorski, Krzysztof and Wegener, Jörg},
  issn         = {0361-0926},
  keyword      = {Kurtosis,Laplace distribution,Method of moment estimation,Moving,averages,Skewness,Stochastic fields},
  language     = {eng},
  number       = {18},
  pages        = {3281--3302},
  publisher    = {Marcel Dekker},
  series       = {Communications in Statistics: Theory and Methods},
  title        = {Estimation for Stochastic Models Driven by Laplace Motion},
  url          = {http://dx.doi.org/10.1080/03610926.2010.499051},
  volume       = {40},
  year         = {2011},
}