Statistical learning for big dependent data /

"This book presents methods useful for analyzing and understanding large data sets that are dynamically dependent. The book will begin with examples of multivariate dependent data and tools for presenting descriptive statistics of such data. It then introduces some useful statistical methods fo...

Description complète

Détails bibliographiques
Cote:Libro Electrónico
Auteurs principaux: Peña, Daniel, 1948- (Auteur), Tsay, Ruey S., 1951- (Auteur)
Format: Électronique eBook
Langue:Inglés
Publié: Hoboken, NJ : John Wiley & Sons, Inc., 2021.
Édition:First edition.
Collection:Wiley series in probability and statistics.
Sujets:
Big data > Mathematics.
Time-series analysis.
Data mining > Statistical methods.
Forecasting > Statistical methods.
Données volumineuses > Mathématiques.
Série chronologique.
Prévision > Méthodes statistiques.
Data mining > Statistical methods
Forecasting > Statistical methods
Time-series analysis
Accès en ligne:Texto completo (Requiere registro previo con correo institucional)
Table des matières:
  • Introduction to big dependent data
  • Linear univariate time series
  • Analysis of multivariate time series
  • Handling heterogeneity in many time series
  • Clustering and classification of time series
  • Dynamic factor models
  • Forecasting with big dependent data
  • Machine learning of big dependent data
  • Spatio-temporal dependent data.

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