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fdaACF  

Autocorrelation Function for Functional Time Series
View on CRAN: Click here


Download and install fdaACF package within the R console
Install from CRAN:
install.packages("fdaACF")

Install from Github:
library("remotes")
install_github("cran/fdaACF")

Install by package version:
library("remotes")
install_version("fdaACF", "1.0.0")



Attach the package and use:
library("fdaACF")
Maintained by
Guillermo Mestre Marcos
[Scholar Profile | Author Map]
First Published: 2020-01-24
Latest Update: 2020-10-20
Description:
Quantify the serial correlation across lags of a given functional time series using the autocorrelation function and a partial autocorrelation function for functional time series proposed in Mestre et al. (2021) . 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.
How to cite:
Guillermo Mestre Marcos (2020). fdaACF: Autocorrelation Function for Functional Time Series. R package version 1.0.0, https://cran.r-project.org/web/packages/fdaACF. Accessed 01 May. 2025.
Previous versions and publish date:
0.1.0 (2020-01-24 18:10), 0.2.0 (2020-08-11 17:00)
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Complete documentation for fdaACF
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