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Spartan random processes in time series modeling

D.T. Hristopulos

Απλή Εγγραφή


URIhttp://purl.tuc.gr/dl/dias/2E470AC4-3AA5-450F-9532-C4F8EDA41181-
Αναγνωριστικόhttps://doi.org/10.1016/j.physa.2008.01.051-
Γλώσσαen-
Μέγεθος6 pagesen
ΤίτλοςSpartan random processes in time series modelingen
ΔημιουργόςD.T. Hristopulosen
ΔημιουργόςM. Zukovicen
ΠερίληψηA 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
ΤύποςPeer-Reviewed Journal Publicationen
ΤύποςΔημοσίευση σε Περιοδικό με Κριτέςel
Άδεια Χρήσηςhttp://creativecommons.org/licenses/by/4.0/en
Ημερομηνία2015-09-25-
Ημερομηνία Δημοσίευσης2007-
Βιβλιογραφική ΑναφοράM.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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