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modeltime.ensemble
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Download and install modeltime.ensemble package within the R console
Install from CRAN:
install.packages("modeltime.ensemble")
Install from Github:
library("remotes")
install_github("cran/modeltime.ensemble") Install by package version:
library("remotes")
install_version("modeltime.ensemble", "1.1.0") Attach the package and use:
library("modeltime.ensemble")
Maintained by
Matt Dancho
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2020-10-07
Latest Update: 2024-07-19
Description:
A 'modeltime' extension that implements time series ensemble forecasting methods including model averaging,
weighted averaging, and stacking. These techniques are popular methods
to improve forecast accuracy and stability. Refer to papers such as
"Machine-Learning Models for Sales Time Series Forecasting" Pavlyshenko, B.M. (2019) .
How to cite:
Matt Dancho (2020). modeltime.ensemble: Ensemble Algorithms for Time Series Forecasting with Modeltime. R package version 1.1.0, https://cran.r-project.org/web/packages/modeltime.ensemble. Accessed 08 Oct. 2026.
Previous versions and publish date:
(2026-07-09 06:32), 0.1.0 (2020-10-07 14:30), 0.2.0 (2020-10-09 12:20), 0.3.0 (2020-11-06 19:00), 0.4.0 (2021-04-05 16:20), 0.4.1 (2021-05-31 08:50), 0.4.2 (2021-07-16 14:10), 1.0.0 (2021-10-19 19:50), 1.0.1 (2022-06-09 14:20), 1.0.2 (2022-10-19 01:02), 1.0.3 (2023-04-18 13:50), 1.0.4 (2024-07-19 17:30), 1.0.5 (2025-08-28 21:10)
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Complete documentation for modeltime.ensemble
Functions, R codes and Examples using
the modeltime.ensemble R package
Some associated functions: ensemble_average . ensemble_model_spec . ensemble_nested_average . ensemble_nested_weighted . ensemble_weighted . pipe . tidyeval .
Some associated R codes: 00_global_variables.R . 00_imports.R . dev-model_descriptions.R . ensemble_average.R . ensemble_model_spec.R . ensemble_weighted.R . modeltime_calibrate.R . modeltime_forecast.R . modeltime_recursive.R . modeltime_refit.R . nested_ensemble_average.R . nested_ensemble_weighted.R . tibble-type_sum.R . utils-parallel_processing.R . utils-pipe.R . utils-tidy-eval.R . Full modeltime.ensemble package functions and examples
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