Autocorrelation Function for Functional Time Series

Quantify the serial correlation across lags of a given functional time series using an autocorrelation function and a partial autocorrelation function for functional time series. The autocorrelation functions are based on the L2 norm of the lagged covariance operators of the series. Functions are available for estimating the distribution of the autocorrelation functions under the assumption of strong functional white noise.


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install.packages("fdaACF")

0.2.0 by Guillermo Mestre Marcos, 2 months ago


https://github.com/GMestreM/fdaACF


Report a bug at https://github.com/GMestreM/fdaACF/issues


Browse source code at https://github.com/cran/fdaACF


Authors: Guillermo Mestre Marcos [aut, cre] , José Portela González [aut] , Gregory Rice [aut] , Antonio Muñoz San Roque [ctb] , Estrella Alonso Pérez [ctb]


Documentation:   PDF Manual  


Task views: Time Series Analysis, Functional Data Analysis


GPL (>= 2) license


Imports CompQuadForm, pracma, fda, Matrix, vars

Suggests testthat, fields


See at CRAN