Package: feasts 0.5.0.9000

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]

feasts_0.5.0.9000.tar.gz
feasts_0.5.0.9000.zip(r-4.7)feasts_0.5.0.9000.zip(r-4.6)feasts_0.5.0.9000.zip(r-4.5)
feasts_0.5.0.9000.tgz(r-4.6-any)feasts_0.5.0.9000.tgz(r-4.5-any)
feasts_0.5.0.9000.tar.gz(r-4.7-any)feasts_0.5.0.9000.tar.gz(r-4.6-any)
feasts_0.5.0.9000.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
feasts/json (API)

# Install 'feasts' in R:

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

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

Pkgdown/docs site:https://feasts.tidyverts.org

On CRAN:

12.25 score 309 stars 9 packages 1.8k scripts 7.7k downloads 42 exports 45 dependencies

Last updated from:6de72d296e. Checks:9 OK. Indexed: yes.

Target	Result	Time
linux-devel-x86_64	OK	201
source / vignettes	OK	373
linux-release-x86_64	OK	206
macos-release-arm64	OK	142
macos-oldrel-arm64	OK	91
windows-devel	OK	178
windows-release	OK	120
windows-oldrel	OK	131
wasm-release	OK	164

Exports:%>%ACF as_tsibble autolayer autoplot box_pierce CCF classical_decomposition coef_hurst cointegration_johansen cointegration_phillips_ouliaris feat_acf feat_intermittent feat_pacf feat_spectral feat_stl gg_arma gg_irf gg_lag gg_season gg_subseries gg_tsdisplay gg_tsresiduals guerrero ljung_box longest_flat_spot n_crossing_points n_flat_spots PACF portmanteau_tests shift_kl_max shift_level_max shift_var_max stat_arch_lm STL unitroot_kpss unitroot_ndiffs unitroot_nsdiffs unitroot_pp var_tiled_mean var_tiled_var X_13ARIMA_SEATS

Dependencies:anytime BH cli cpp11 digest distributional dplyr fabletools farver generics ggdist ggplot2 ggtime glue gtable isoband labeling lifecycle lubridate magrittr numDeriv pillar pkgconfig progressr purrr quadprog R6 RColorBrewer Rcpp rlang S7 scales slider stringi stringr tibble tidyr tidyselect timechange tsibble utf8 vctrs viridisLite warp withr

Introduction to feasts

Rendered fromfeasts.Rmdusingknitr::rmarkdown

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

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
feasts: Feature Extraction and Statistics for Time Series	feasts-package feasts
(Partial) Autocorrelation and Cross-Correlation Function Estimation	ACF CCF PACF
Classical Seasonal Decomposition by Moving Averages	classical_decomposition
Hurst coefficient	coef_hurst
Johansen Procedure for VAR	cointegration_johansen
Phillips and Ouliaris Cointegration Features	cointegration_phillips_ouliaris
Autocorrelation-based features	feat_acf
Intermittency features	feat_intermittent
Partial autocorrelation-based features	feat_pacf
Spectral features of a time series	feat_spectral
STL features	feat_stl
Generate block bootstrapped series from an STL decomposition	generate.stl_decomposition
Guerrero's method for Box Cox lambda selection	guerrero
Portmanteau tests	box_pierce ljung_box portmanteau_tests
Longest flat spot length	longest_flat_spot n_flat_spots
Number of crossing points	n_crossing_points
Sliding window features	shift_kl_max shift_level_max shift_var_max
ARCH LM Statistic	stat_arch_lm
Multiple seasonal decomposition by Loess	STL
Unit root tests	unitroot_kpss unitroot_pp
Number of differences required for a stationary series	unitroot_ndiffs unitroot_nsdiffs
Time series features based on tiled windows	var_tiled_mean var_tiled_var
X-13ARIMA-SEATS Seasonal Adjustment	X_13ARIMA_SEATS