Package: hdftsa 1.1

Han Lin Shang

hdftsa: High-Dimensional Functional Time Series Analysis

Offers methods for visualising, modelling, and forecasting high-dimensional functional time series, also known as functional panel data. Documentation about 'hdftsa' is initially provided via the paper by Cristian F. Jimenez-Varon, Ying Sun and Han Lin Shang (2024, Journal of Computational and Graphical Statistics).

Authors:Han Lin Shang [aut, cre]

hdftsa_1.1.tar.gz
hdftsa_1.1.tar.gz(r-4.7-any)hdftsa_1.1.tar.gz(r-4.6-any)
hdftsa_1.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
hdftsa/json (API)

# Install 'hdftsa' in R:
install.packages('hdftsa', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))
Datasets:
  • all_hmd_female_data - The US female log-mortality rate from 1959-2020 and 3 states (New York, California, Illinois).
  • all_hmd_male_data - The US male log-mortality rate from 1959-2020 and 3 states (New York, California, Illinois).
  • hd_data - Simulated high-dimensional functional time series
  • sim_ex_cluster - Simulated multiple sets of functional time series
  • sim_ex_cluster.smooth - Simulated multiple sets of functional time series

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

1.00 score 274 downloads 13 exports 125 dependencies

Last updated from:9b65ef832a. Checks:4 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK204
source / vignettesOK202
linux-release-x86_64OK204
wasm-releaseOK185

Exports:dmfpcaforecast.hdfpcahdfpcaMFPCAmftscOne_way_meanOne_way_mean_residualsOne_way_median_polishOne_way_median_polish_residualsTwo_way_meanTwo_way_mean_residualsTwo_way_median_polishTwo_way_median_polish_residuals

Dependencies:abindashbackportsbase64encbitopsbootbslibcachemcheckmateclasscliclustercolorspacecpp11cvardata.tabledeSolvedigeste1071ecpevaluateevgamfarverfastICAfastmapfBasicsfdafdapacefdsfGarchFNNfontawesomeforecastforeignFormulafracdifffsftsagbutilsgenericsgeometryggplot2glueGPArotationgridExtragssgtablehdrcdehighrHmischtmlTablehtmltoolshtmlwidgetsisobandjquerylibjsonlitekernlabKernSmoothknitrkslabelingLaplacesDemonlatticelifecyclelinprogLmomentslmtestlocfitlpSolvemagicmagrittrMASSMatrixmclustmemoisemgcvmimemnormtmulticoolmvtnormnlmennetnumDerivpcaPPpdfClusterpracmaproxypsychR6rainbowrappdirsrbibutilsRColorBrewerRcppRcppArmadilloRcppEigenRcppProgressRCurlRdpackrlangrmarkdownROOPSDrpartrstudioapiS7sandwichsassscalessdespatialstablediststringistringrstrucchangetimeDatetimeSeriestinytexurcavarsvctrsviridisLitewithrxfunyamlzoo

Readme and manuals

Help Manual

Help pageTopics
High-dimensional Functional Time Series Analysishdftsa-package hdftsa
The US female log-mortality rate from 1959-2020 and 3 states (New York, California, Illinois).all_hmd_female_data
The US male log-mortality rate from 1959-2020 and 3 states (New York, California, Illinois).all_hmd_male_data
Dynamic multilevel functional principal component analysisdmfpca
Forecasting via a high-dimensional functional principal component regressionforecast.hdfpca
Simulated high-dimensional functional time serieshd_data
High-dimensional functional principal component analysishdfpca
Multilevel functional principal component analysis for clusteringMFPCA
Multiple functional time series clusteringmftsc
One-way functional analysis of variance based on meansOne_way_mean
High-dimensional functional time series decomposition into deterministic and functional residual components.One_way_mean_residuals
One-way functional median polish from Sun and Genton (2012)One_way_median_polish
High-dimensional functional time series decomposition into deterministic (from functional median polish of Sun and Genton (2012)), and functional residual components.One_way_median_polish_residuals
Simulated multiple sets of functional time seriessim_ex_cluster sim_ex_cluster.smooth
Functional analysis of variance fitted by means.Two_way_mean
Functional time series decomposition into deterministic (functional analysis of variance fitted by means), and time-varying components (functional residuals).Two_way_mean_residuals
Two-way functional median polish from Sun and Genton (2012)Two_way_median_polish
Functional time series decomposition into deterministic (from functional median polish from Sun and Genton (2012)), and time-varying components (functional residuals).Two_way_median_polish_residuals