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:
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fdaACF.pdf |fdaACF.html✨
fdaACF/json (API)
NEWS
| # 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
- elec_prices - Daily electricity price profiles from the Day-Ahead Spanish Electricity Market
Last updated 4 years agofrom:d660e57355. Checks:OK: 1 NOTE: 6. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Nov 01 2024 |
| R-4.5-win | NOTE | Nov 01 2024 |
| R-4.5-linux | NOTE | Nov 01 2024 |
| R-4.4-win | NOTE | Nov 01 2024 |
| R-4.4-mac | NOTE | Nov 01 2024 |
| R-4.3-win | NOTE | Nov 01 2024 |
| R-4.3-mac | NOTE | Nov 01 2024 |
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:ashbitopscliclustercolorspaceCompQuadFormdeSolvefansifarverfdafdsFNNggplot2gluegtablehdrcdeisobandkernlabKernSmoothkslabelinglatticelifecyclelmtestlocfitmagrittrMASSMatrixmclustmgcvmulticoolmunsellmvtnormnlmepcaPPpillarpkgconfigpracmaR6rainbowRColorBrewerRcppRCurlrlangsandwichscalesstrucchangetibbleurcautf8varsvctrsviridisLitewithrzoo
