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: | 0.0.2 |
| Depends: | R (≥ 3.5.0) |
| Imports: | timetk (≥ 2.1.0), parsnip (≥ 0.1.2), dials, yardstick, workflows, hardhat, rlang (≥ 0.1.2), glue, plotly, reactable, gt, ggplot2, tibble, tidyr, dplyr, purrr, stringr, forcats, scales, janitor, progressr, magrittr, forecast, xgboost, prophet, methods |
| Suggests: | tidymodels, recipes, rsample, tune, tidyverse, lubridate, testthat, roxygen2, kernlab, earth, randomForest, tidyquant, knitr, rmarkdown |
| Published: | 2020-07-03 |
| 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 |
| CRAN checks: | modeltime results |
| Reference manual: | modeltime.pdf |
| Vignettes: |
Extending Modeltime Getting Started with Modeltime Modeltime Model List |
| Package source: | modeltime_0.0.2.tar.gz |
| Windows binaries: | r-devel: modeltime_0.0.2.zip, r-release: modeltime_0.0.2.zip, r-oldrel: modeltime_0.0.2.zip |
| macOS binaries: | r-release: modeltime_0.0.2.tgz, r-oldrel: modeltime_0.0.2.tgz |
| Old sources: | modeltime archive |
| Reverse suggests: | timetk |
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