Package: feasts 0.4.1

Mitchell OHara-Wild

feasts: Feature Extraction and Statistics for Time Series

Provides a collection of features, decomposition methods, statistical summaries and graphics functions for the analysing tidy time series data. The package name 'feasts' is an acronym comprising of its key features: Feature Extraction And Statistics for Time Series.

Authors:Mitchell O'Hara-Wild [aut, cre], Rob Hyndman [aut], Earo Wang [aut], Di Cook [ctb], Thiyanga Talagala [ctb], Leanne Chhay [ctb]

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feasts.pdf |feasts.html✨
feasts/json (API)
NEWS

# Install 'feasts' in R:
install.packages('feasts', repos = c('https://tidyverts.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/tidyverts/feasts/issues

On CRAN:

12.54 score 295 stars 7 packages 1.2k scripts 17k downloads 43 exports 52 dependencies

Last updated 1 months agofrom:3590f13c9d. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKOct 25 2024
R-4.5-winOKOct 25 2024
R-4.5-linuxOKOct 25 2024
R-4.4-winOKOct 25 2024
R-4.4-macOKOct 25 2024
R-4.3-winOKOct 25 2024
R-4.3-macOKOct 25 2024

Exports:%>%ACFas_tsibbleautolayerautoplotbox_pierceCCFclassical_decompositioncoef_hurstcointegration_johansencointegration_phillips_ouliarisfeat_acffeat_intermittentfeat_pacffeat_spectralfeat_stlgg_armagg_irfgg_laggg_seasongg_subseriesgg_tsdisplaygg_tsresidualsguerreroljung_boxlongest_flat_spotn_crossing_pointsn_flat_spotsPACFportmanteau_testsscale_x_cf_lagshift_kl_maxshift_level_maxshift_var_maxstat_arch_lmSTLunitroot_kpssunitroot_ndiffsunitroot_nsdiffsunitroot_ppvar_tiled_meanvar_tiled_varX_13ARIMA_SEATS

Dependencies:anytimeBHclicolorspacecpp11digestdistributionaldplyrellipsisfabletoolsfansifarvergenericsggdistggplot2gluegtableisobandlabelinglatticelifecyclelubridatemagrittrMASSMatrixmgcvmunsellnlmenumDerivpillarpkgconfigprogressrpurrrquadprogR6RColorBrewerRcpprlangscalessliderstringistringrtibbletidyrtidyselecttimechangetsibbleutf8vctrsviridisLitewarpwithr

Introduction to feasts

Rendered fromfeasts.Rmdusingknitr::rmarkdownon Oct 25 2024.

Last update: 2020-06-17
Started: 2019-08-02

Readme and manuals

Help Manual

Help pageTopics
feasts: Feature Extraction and Statistics for Time Seriesfeasts-package feasts
(Partial) Autocorrelation and Cross-Correlation Function EstimationACF CCF PACF
Auto- and Cross- Covariance and -Correlation plotsautoplot.tbl_cf
Classical Seasonal Decomposition by Moving Averagesclassical_decomposition
Hurst coefficientcoef_hurst
Johansen Procedure for VARcointegration_johansen
Phillips and Ouliaris Cointegration Testcointegration_phillips_ouliaris
Autocorrelation-based featuresfeat_acf
Intermittency featuresfeat_intermittent
Partial autocorrelation-based featuresfeat_pacf
Spectral features of a time seriesfeat_spectral
STL featuresfeat_stl
Generate block bootstrapped series from an STL decompositiongenerate.stl_decomposition
Plot characteristic ARMA rootsgg_arma
Plot impulse response functionsgg_irf
Lag plotsgg_lag
Seasonal plotgg_season
Seasonal subseries plotsgg_subseries
Ensemble of time series displaysgg_tsdisplay
Ensemble of time series residual diagnostic plotsgg_tsresiduals
Guerrero's method for Box Cox lambda selectionguerrero
Portmanteau testsbox_pierce ljung_box portmanteau_tests
Longest flat spot lengthlongest_flat_spot n_flat_spots
Number of crossing pointsn_crossing_points
Sliding window featuresshift_kl_max shift_level_max shift_var_max
ARCH LM Statisticstat_arch_lm
Multiple seasonal decomposition by LoessSTL
Unit root testsunitroot_kpss unitroot_pp
Number of differences required for a stationary seriesunitroot_ndiffs unitroot_nsdiffs
Time series features based on tiled windowsvar_tiled_mean var_tiled_var
X-13ARIMA-SEATS Seasonal AdjustmentX_13ARIMA_SEATS