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Auteur Richard A. Davis |
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Titre : Introduction to Time Series and Forecasting Type de document : Monographie Auteurs : Peter J. Brockwell, Auteur ; Richard A. Davis, Auteur Editeur : Springer International Publishing Année de publication : 2016 Importance : 425 p. Format : 21 x 28 cm ISBN/ISSN/EAN : 978-3-319-29854-2 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Statistiques
[Termes IGN] analyse spectrale
[Termes IGN] calcul matriciel
[Termes IGN] matrice de covariance
[Termes IGN] méthode du maximum de vraisemblance (estimation)
[Termes IGN] modèle de simulation
[Termes IGN] modèle stochastique
[Termes IGN] série temporelle
[Termes IGN] variable aléatoireRésumé : (éditeur) This book is aimed at the reader who wishes to gain a working knowledge of time series and forecasting methods as applied to economics, engineering and the natural and social sciences. It assumes knowledge only of basic calculus, matrix algebra and elementary statistics. This third edition contains detailed instructions for the use of the professional version of the Windows-based computer package ITSM2000, now available as a free download from the Springer Extras website. The logic and tools of time series model-building are developed in detail. Numerous exercises are included and the software can be used to analyze and forecast data sets of the user's own choosing. The book can also be used in conjunction with other time series packages such as those included in R. The programs in ITSM2000 however are menu-driven and can be used with minimal investment of time in the computational details. The core of the book covers stationary processes, ARMA and ARIMA processes, multivariate time series and state-space models, with an optional chapter on spectral analysis. Many additional special topics are also covered. Note de contenu : 1- Introduction
2- Stationary Processes
3- ARMA Models
4- Spectral Analysis
5- Modeling and Forecasting with ARMA Processes
6- Nonstationary and Seasonal Time Series Models
7- Time Series Models for Financial Data
8- Multivariate Time Series
9- State-Space Models
10- Forecasting Techniques
11- Further TopicsNuméro de notice : 25750 Affiliation des auteurs : non IGN Thématique : MATHEMATIQUE Nature : Monographie En ligne : https://link.springer.com/book/10.1007%2F978-3-319-29854-2 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94942