Autocorrelation Function for Functional Time Series
Overview
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) doi:10.1016/j.csda.2020.107108. 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.
New functionalities added in this release:
- Add function FTS_identification. This function is a wrapper for functions obtain_FACF and obtain_FPACF, and shows both the FACF and the FPACF of a given functional time series.
- Add citation information for the paper "Functional time series model identification and diagnosis by means of auto- and partial autocorrelation analysis" <doi:10.1016/j.csda.2020.107108>. This paper contains the theoretical foundations of the autocorrelation functions implemented in this package.
- Fix minor bugs present in version 0.2.0.
From NEWS.md in the release
Install
Health
NOTECRAN incoming feasibilityr-devel-linux-x86_64-debian-clang, r-devel-linux-x86_64-debian-gcc
Maintainer: ‘Guillermo Mestre Marcos <guillermo.mestre@comillas.edu>’
Package CITATION file contains call(s) to old-style personList() or
as.personList(). Please use c() on person objects instead.
Package CITATION file contains call(s) to old-style citEntry(). Please
use bibentry() instead.
Found the following URLs which should use \doi (with the DOI name only):
File ‘FTS_identification.Rd’:
https://doi.org/10.1016/j.csda.2020.107108
https://doi.org/10.1016/j.ijepes.2020.106083
https://doi.org/10.1016/j.jmva.2017.08.004
File ‘fit_ARHp_FPCA.Rd’:
https://doi.org/10.1080/01621459.2014.909317
File ‘obtain_FACF.Rd’:
https://doi.org/10.1016/j.csda.2020.107108
https://doi.org/10.1016/j.ijepes.2020.106083
https://doi.org/10.1016/j.jmva.2017.08.004
File ‘obtain_FPACF.Rd’:
https://doi.org/10.1016/j.csda.2020.107108- NOTE11 OK, 2 NOTE2026-06-09
- ERROR11 OK, 1 NOTE, 1 ERROR2026-06-08
- NOTE12 OK, 2 NOTE2026-03-10
Documentation
- Help pages
- 19includes a package overview page
- Examples that run
- 100%17 run in a plain check
- Exported functions with examples
- 100%
- Documented parameters
- 88%
- Return-value docs
- 82%
- Help pages citing references
- 21%
Downloads
Repository
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Checks run against github.com/gmestrem/fdaacf on 2026-10-11.
Dependencies
Code & Tests
Datasets
People & History
Pick two releases to compare their code metrics.
- RR 4.6.0 released · 2026-04-24
- RR 4.5.0 released · 2025-04-11
- RR 4.4.0 released · 2024-04-24
- RR 4.3.0 released · 2023-04-21
- RR 4.2.0 released · 2022-04-22
- RR 4.1.0 released · 2021-05-18
- 1.0.0Latest
- 0.2.02020-08-11 · diff ↗ ·
added 5 exports
fit_ARHp_FPCA, integral_operator, mat2fd, obtain_FPACF, reconstruct_fd_from_PCA - RR 4.0.0 released · 2020-04-24
- 0.1.02020-01-24
- RR 3.6.0 released · 2019-04-26
Package metadata
- First published
- 2020-01-24
- Total releases
- 3 / 6 yrs
- License
- GPL (>= 2) OSI
- Minimum R
- ≥ 3.5.0
- Bundled data
- 20 KB / 1 file
- Download size
- 43 KB
Cite
Cite this package
Run in R for the authors' entry:
citation("fdaACF")The package provides a citation file, so citation() returns the authors' own entry.
It points to 10.1016/j.csda.2020.107108.
Cite the R Observatory
For a number measured here: a download total, a coverage figure, an archival date.
From data release v2026-10-18, which the citation names so these numbers can be found later. More on citing and the projects behind them.