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Spartan random processes in time series modeling

D.T. Hristopulos

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URIhttp://purl.tuc.gr/dl/dias/2E470AC4-3AA5-450F-9532-C4F8EDA41181-
Identifierhttps://doi.org/10.1016/j.physa.2008.01.051-
Languageen-
Extent6 pagesen
TitleSpartan random processes in time series modelingen
CreatorD.T. Hristopulosen
CreatorM. Zukovicen
Content SummaryA Spartan random process (SRP) is used to estimate the correlation structure of time series and to predict (extrapolate) the data values. SRP's are motivated from statistical physics, and they can be viewed as Ginzburg-Landau models. The temporal correlations of the SRP are modeled in terms of `interactions' between the field values. Model parameter inference employs the computationally fast modified method of moments, which is based on matching sample energy moments with the respective stochastic constraints. The parameters thus inferred are then compared with those obtained by means of the maximum likelihood method. The performance of the Spartan predictor (SP) is investigated using real time series of the quarterly S&P 500 index. SP prediction errors are compared with those of the Kolmogorov-Wiener predictor. Two predictors, one of which explicit, are derived and used for extrapolation. The performance of the predictors is similarly evaluated.en
Type of ItemPeer-Reviewed Journal Publicationen
Type of ItemΔημοσίευση σε Περιοδικό με Κριτέςel
Licensehttp://creativecommons.org/licenses/by/4.0/en
Date of Item2015-09-25-
Date of Publication2007-
Bibliographic CitationM.Zukovic , D.T. Hristopulos , "Spartan random processes in time series modeling , Ph. A-Stat. Mecha. An. Its Appl., vol.387 ,no. 15, pp.3995-4001,2007.doi :10.1016/j.physa.2008.01.051en

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