Now showing items 1-4 of 4

    • Functional time series identification and diagnosis by means of autocorrelation analysis 

      Mestre Marcos, Guillermo; Portela González, José; Rice, Gregory; Muñoz San Roque, Antonio; Alonso Pérez, Estrella
      Quantifying the serial correlation across lags is a crucial step in the identification and diagnosis of a model for scalar time series, where the autocorrelation and partial autocorrelation functions of the time series are ...
    • Functional time series identification and diagnosis by means of autocorrelation analysis 

      Mestre Marcos, Guillermo; Portela González, José; Rice, Gregory; Muñoz San Roque, Antonio; Alonso Pérez, Estrella (Sociedad de Estadística e Investigación Operativa; Universitat Politècnica de València (Alcoy, España), 03/09/2019)
      Quantifying the serial correlation across lags is a crucial step in the identification and diagnosis of a model for scalar time series, where the autocorrelation and partial autocorrelation functions of the time series are ...
    • Functional time series identification and diagnosis by means of autocorrelation analysis 

      Mestre Marcos, Guillermo; Portela González, José; Rice, Gregory; Muñoz San Roque, Antonio; Alonso Pérez, Estrella
      Quantifying the serial correlation across lags is a crucial step in the identification and diagnosis of a model for scalar time series, where the autocorrelation and partial autocorrelation functions of the time series are ...
    • Functional time series model identification and diagnosis by means of auto- and partial autocorrelation analysis 

      Mestre Marcos, Guillermo; Portela González, José; Rice, Gregory; Muñoz San Roque, Antonio; Alonso Pérez, Estrella (2021-03-01)
      Quantifying the serial correlation across time lags is a crucial step in the identification and diagnosis of a time series model. Simple and partial autocorrelation functions of the time series are the most widely used ...