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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Detalles Bibliográficos
Otros Autores: Peña, Daniel, 1948- author (author), Tsay, Ruey S., 1951- author
Formato: Libro electrónico
Idioma:Inglés
Publicado: Hoboken, New Jersey : Wiley [2021]
Edición:First edition
Colección:Wiley series in probability and statistics.
Materias:
Ver en Biblioteca Universitat Ramon Llull:https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009645699406719
Tabla de Contenidos:
  • 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.