timetk: A Tool Kit for Working with Time Series in R

Easy visualization, wrangling, and feature engineering of time series data for forecasting and machine learning prediction. Consolidates and extends time series functionality from packages including 'dplyr', 'stats', 'xts', 'forecast', 'slider', 'padr', 'recipes', and 'rsample'.

Version: 2.8.1
Depends: R (≥ 3.3.0)
Imports: recipes (≥ 0.2.0), rsample, dplyr (≥ 1.0.0), ggplot2, forcats, stringr, plotly, lubridate (≥ 1.6.0), padr (≥ 0.5.2), purrr (≥ 0.2.2), readr (≥ 1.3.0), stringi (≥ 1.4.6), tibble (≥ 3.0.3), tidyr (≥ 1.1.0), xts (≥ 0.9-7), zoo (≥ 1.7-14), rlang (≥ 0.4.7), tidyselect (≥ 1.1.0), slider, anytime, timeDate, forecast, tsfeatures, hms, assertthat, generics
Suggests: tidyquant, tidymodels, modeltime, workflows, parsnip, tune, yardstick, tidyverse, knitr, rmarkdown, robets, broom, scales, testthat, fracdiff, timeSeries, tseries, trelliscopejs, roxygen2, covr
Published: 2022-05-31
Author: Matt Dancho [aut, cre], Davis Vaughan [aut]
Maintainer: Matt Dancho <mdancho at business-science.io>
BugReports: https://github.com/business-science/timetk/issues
License: GPL (≥ 3)
URL: https://github.com/business-science/timetk, https://business-science.github.io/timetk/
NeedsCompilation: no
Materials: README NEWS
In views: TimeSeries
CRAN checks: timetk results

Documentation:

Reference manual: timetk.pdf
Vignettes: Visualizing Time Series
Time Series Data Wrangling

Downloads:

Package source: timetk_2.8.1.tar.gz
Windows binaries: r-devel: timetk_2.8.1.zip, r-release: timetk_2.8.1.zip, r-oldrel: timetk_2.8.1.zip
macOS binaries: r-release (arm64): timetk_2.8.1.tgz, r-oldrel (arm64): timetk_2.8.1.tgz, r-release (x86_64): timetk_2.8.1.tgz, r-oldrel (x86_64): timetk_2.8.1.tgz
Old sources: timetk archive

Reverse dependencies:

Reverse imports: activatr, alphavantager, anomalize, finnts, healthyR, healthyR.ts, modeltime, modeltime.ensemble, modeltime.gluonts, modeltime.h2o, modeltime.resample, PortalHacienda, RTL, sweep, tidyquant
Reverse suggests: cleanTS, healthyR.ai, iForecast, sknifedatar

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