Prediction in time series regression models / Frantisek Stulajter (2002)

Public ISBD Titre : Prediction in time series regression models Type de document : texte imprimé Auteurs : Frantisek Stulajter, Auteur Editeur : Berlin ; London ; Cham : Springer Année de publication : 2002 Importance : VIII-231 p. Présentation : ill. Format : 25 cm ISBN/ISSN/EAN : 978-0-387-95350-2 Note générale : Bibliogr. p. [223]-227. Index Langues : Français (fre) Mots-clés : Time-series analysis Regression analysis Processus stochastiques Séries chronologiques Analyse de régression Index. décimale : 519.22 Théorie statistique. Modèles statistiques. Statistiques mathématiques Résumé : This book deal with the statiscal analysis of time series and covers situations that do not fit into the framework of stationary time series, as other. Estimators and their properties are presented for regression parametres of reqression model describing linearly or nonlinearly the mean and the covariance functions of general time series. Using these models, a cohesive theory and methods of predictions of time series are developed. The methods are useful for all application where trend and oscillations of time correlated data should be carfully modeled, e.g., ecology, econometrics, and finance series. Note de contenu : Contents *Basic Mathematics and Statistics *Random Processes and Time Series *Estimation of Time Series Parameters *Predictions in Time Series *Empirical Predictors Prediction in time series regression models [texte imprimé] / Frantisek Stulajter, Auteur . - Berlin ; London ; Cham : Springer, 2002 . - VIII-231 p. : ill. ; 25 cm. ISBN : 978-0-387-95350-2 Bibliogr. p. [223]-227. Index Langues : Français (fre) Mots-clés : Time-series analysis Regression analysis Processus stochastiques Séries chronologiques Analyse de régression Index. décimale : 519.22 Théorie statistique. Modèles statistiques. Statistiques mathématiques Résumé : This book deal with the statiscal analysis of time series and covers situations that do not fit into the framework of stationary time series, as other. Estimators and their properties are presented for regression parametres of reqression model describing linearly or nonlinearly the mean and the covariance functions of general time series. Using these models, a cohesive theory and methods of predictions of time series are developed. The methods are useful for all application where trend and oscillations of time correlated data should be carfully modeled, e.g., ecology, econometrics, and finance series. Note de contenu : Contents *Basic Mathematics and Statistics *Random Processes and Time Series *Estimation of Time Series Parameters *Predictions in Time Series *Empirical Predictors

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Code-barres	Cote	Support	Localisation	Section	Disponibilité	Etat_Exemplaire
047527	519.22 STU	Papier	Bibliothèque Centrale	Mathématiques	Disponible