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.facebook.com/blog/2017/02/prophet-forecasting-at-scale/>.).
Version:
1.3.2
Depends:
R (≥ 3.5.0)
Imports:
StanHeaders,
timetk (≥ 2.8.1),
parsnip (≥ 0.2.1),
dials,
yardstick (≥ 0.0.8),
workflows (≥ 1.0.0),
hardhat (≥ 1.0.0),
rlang (≥ 0.1.2),
glue,
plotly,
reactable,
gt,
ggplot2,
tibble,
tidyr,
dplyr (≥ 1.1.0),
purrr,
stringr,
forcats,
scales,
janitor, parallel,
parallelly,
doParallel,
foreach,
magrittr,
forecast,
xgboost (≥ 1.2.0.1),
prophet, methods,
cli,
tidymodels
Suggests:
rstan,
slider,
sparklyr,
workflowsets,
recipes,
rsample,
tune (≥ 0.2.0),
lubridate,
testthat,
kernlab,
glmnet,
thief,
smooth,
greybox,
earth,
randomForest,
trelliscopejs,
knitr,
rmarkdown (≥ 2.9),
webshot,
qpdf,
TSrepr,
future,
doFuture
Published:
2025年08月28日
Author:
Matt Dancho [aut, cre],
Business Science [cph]
Maintainer:
Matt Dancho <mdancho at business-science.io>
NeedsCompilation:
no
Documentation:
Downloads:
Reverse dependencies:
Linking:
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