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]

fdaACF_1.0.0.tar.gz
fdaACF_1.0.0.zip(r-4.7-any)fdaACF_1.0.0.zip(r-4.6-any)fdaACF_1.0.0.zip(r-4.5-any)
fdaACF_1.0.0.tgz(r-4.6-any)fdaACF_1.0.0.tgz(r-4.5-any)
fdaACF_1.0.0.tar.gz(r-4.7-any)fdaACF_1.0.0.tar.gz(r-4.6-any)
fdaACF_1.0.0.tgz(r-4.6-emscripten)
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:

Conda:

3.60 score 8 stars 4 scripts 336 downloads 17 exports 50 dependencies

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

TargetResultTimeFilesSyslog
linux-develNOTE133
source / vignettesOK177
linux-releaseNOTE136
macos-releaseNOTE179
macos-oldrelNOTE185
windows-develNOTE81
windows-releaseNOTE62
windows-oldrelNOTE72
wasm-releaseOK115

Exports:estimate_iid_distr_Imhofestimate_iid_distr_MCfit_ARHp_FPCAFTS_identificationintegral_operatormat2fdobtain_autocorrelationobtain_autocov_eigenvaluesobtain_autocovarianceobtain_FACFobtain_FPACFobtain_suface_L2_normplot_autocovarianceplot_FACFreconstruct_fd_from_PCAsimulate_iid_brownian_bridgesimulate_iid_brownian_motion

Dependencies:ashbitopscliclustercolorspaceCompQuadFormcpp11deSolvefarverfdafdsFNNggplot2gluegtablehdrcdeisobandkernlabKernSmoothkslabelinglatticelifecyclelmtestlocfitMASSMatrixmclustmgcvmulticoolmvtnormnlmepcaPPpracmaR6rainbowRColorBrewerRcppRCurlrlangS7sandwichscalesstrucchangeurcavarsvctrsviridisLitewithrzoo