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...

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Bibliographic Details
Call Number:Libro Electrónico
Main Authors: Peña, Daniel, 1948- (Author), Tsay, Ruey S., 1951- (Author)
Format: Electronic eBook
Language:Inglés
Published: Hoboken, NJ : John Wiley & Sons, Inc., 2021.
Edition:First edition.
Series:Wiley series in probability and statistics.
Subjects:
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
Online Access:Texto completo (Requiere registro previo con correo institucional)
Table of Contents:
  • 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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