Package: fdaACF 1.0.0

Guillermo Mestre Marcos

fdaACF: Autocorrelation Function for Functional Time Series

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.

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

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manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
fdaACF/json (API)

# Install 'fdaACF' in R:

install.packages('fdaACF', repos = c('https://gmestrem.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/gmestrem/fdaacf/issues

Datasets:

elec_prices - Daily electricity price profiles from the Day-Ahead Spanish Electricity Market

On CRAN:

3.64 score 8 stars 11 scripts 290 downloads 17 exports 50 dependencies

Last updated from:d660e57355. Checks:7 NOTE, 2 OK. Indexed: yes.

Target	Result	Time
linux-devel-x86_64	NOTE	148
source / vignettes	OK	159
linux-release-x86_64	NOTE	133
macos-release-arm64	NOTE	143
macos-oldrel-arm64	NOTE	129
windows-devel	NOTE	81
windows-release	NOTE	113
windows-oldrel	NOTE	94
wasm-release	OK	126

Exports:estimate_iid_distr_Imhof estimate_iid_distr_MC fit_ARHp_FPCA FTS_identification integral_operator mat2fd obtain_autocorrelation obtain_autocov_eigenvalues obtain_autocovariance obtain_FACF obtain_FPACF obtain_suface_L2_norm plot_autocovariance plot_FACF reconstruct_fd_from_PCA simulate_iid_brownian_bridge simulate_iid_brownian_motion

Dependencies:ash bitops cli cluster colorspace CompQuadForm cpp11 deSolve farver fda fds FNN ggplot2 glue gtable hdrcde isoband kernlab KernSmooth ks labeling lattice lifecycle lmtest locfit MASS Matrix mclust mgcv multicool mvtnorm nlme pcaPP pracma R6 rainbow RColorBrewer Rcpp RCurl rlang S7 sandwich scales strucchange urca vars vctrs viridisLite withr zoo

Help page	Topics
Daily electricity price profiles from the Day-Ahead Spanish Electricity Market	elec_prices
Estimate distribution of the fACF under the iid. hypothesis using Imhof's method	estimate_iid_distr_Imhof
Estimate distribution of the fACF under the iid. hypothesis using MC method	estimate_iid_distr_MC
fdaACF: Autocorrelation function for Functional Time Series	fdaACF
Fit an ARH(p) to a given functional time series	fit_ARHp_FPCA
Obtain the auto- and partial autocorrelation functions for a given FTS	FTS_identification
Integral transformation of a curve using an integral operator	integral_operator
Obtain a fd object from a matrix	mat2fd
Estimate the autocorrelation function of the series	obtain_autocorrelation
Estimate eigenvalues of the autocovariance function	obtain_autocov_eigenvalues
Estimate the autocovariance function of the series	obtain_autocovariance
Obtain the autocorrelation function for a given functional time series.	obtain_FACF
Obtain the partial autocorrelation function for a given FTS.	obtain_FPACF
Obtain L2 norm of the autocovariance functions	obtain_suface_L2_norm
Generate a 3D plot of the autocovariance surface of a given FTS	plot_autocovariance
Plot the autocorrelation function of a given FTS	plot_FACF
Obtain the reconstructed curves after PCA	reconstruct_fd_from_PCA
Simulate a FTS from a brownian bridge process	simulate_iid_brownian_bridge
Simulate a FTS from a brownian motion process	simulate_iid_brownian_motion

Package: fdaACF 1.0.0

fdaACF: Autocorrelation Function for Functional Time Series

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