modeltime: The Tidymodels Extension for Time Series Modeling

The time series forecasting framework for use with the 'tidymodels' ecosystem. Models include ARIMA, Exponential Smoothing, and additional time series models from the 'forecast' and 'prophet' packages. Refer to "Forecasting Principles & Practice, Second edition" (<https://otexts.com/fpp2/>). Refer to "Prophet: forecasting at scale" (<https://research.fb.com/blog/2017/02/prophet-forecasting-at-scale/>.).

Version: 0.3.1
Depends: R (≥ 3.5.0)
Imports: StanHeaders, timetk (≥ 2.5.0), parsnip (≥ 0.1.4), dials, yardstick, workflows (≥ 0.1.3), hardhat, rlang (≥ 0.1.2), glue, plotly, reactable, gt, ggplot2, tibble, tidyr, dplyr, purrr, stringr, forcats, scales, janitor, progressr, magrittr, forecast, xgboost (≥ 1.2.0.1), prophet, methods, cli
Suggests: rstan, tidymodels, recipes, rsample, tune, tidyverse, lubridate, testthat, roxygen2, kernlab, earth, randomForest, tidyquant, knitr, rmarkdown, webshot
Published: 2020-11-09
Author: Matt Dancho [aut, cre], Business Science [cph]
Maintainer: Matt Dancho <mdancho at business-science.io>
BugReports: https://github.com/business-science/modeltime/issues
License: MIT + file LICENSE
URL: https://github.com/business-science/modeltime
NeedsCompilation: no
Materials: README NEWS
In views: TimeSeries
CRAN checks: modeltime results

Downloads:

Reference manual: modeltime.pdf
Vignettes: Extending Modeltime
Getting Started with Modeltime
Package source: modeltime_0.3.1.tar.gz
Windows binaries: r-devel: modeltime_0.3.1.zip, r-release: modeltime_0.3.1.zip, r-oldrel: modeltime_0.3.1.zip
macOS binaries: r-release: modeltime_0.3.1.tgz, r-oldrel: modeltime_0.3.1.tgz
Old sources: modeltime archive

Reverse dependencies:

Reverse depends: modeltime.ensemble, modeltime.resample
Reverse suggests: timetk

Linking:

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