Other packages > Find by keyword >

modeltime  

The Tidymodels Extension for Time Series Modeling
View on CRAN: Click here


Download and install modeltime package within the R console
Install from CRAN:
install.packages("modeltime")

Install from Github:
library("remotes")
install_github("cran/modeltime")

Install by package version:
library("remotes")
install_version("modeltime", "1.3.1")



Attach the package and use:
library("modeltime")
Maintained by
Matt Dancho
[Scholar Profile | Author Map]
First Published: 2020-06-22
Latest Update: 2023-09-02
Description:
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" (). Refer to "Prophet: forecasting at scale" (.).
How to cite:
Matt Dancho (2020). modeltime: The Tidymodels Extension for Time Series Modeling. R package version 1.3.1, https://cran.r-project.org/web/packages/modeltime. Accessed 07 May. 2025.
Previous versions and publish date:
0.0.1 (2020-06-22 12:00), 0.0.2 (2020-07-03 22:10), 0.1.0 (2020-09-02 19:50), 0.2.0 (2020-09-28 14:40), 0.2.1 (2020-10-08 19:10), 0.3.0 (2020-10-28 15:00), 0.3.1 (2020-11-09 22:50), 0.4.0 (2020-11-23 09:50), 0.4.1 (2021-01-17 15:30), 0.4.2 (2021-03-19 06:20), 0.5.0 (2021-03-29 18:30), 0.5.1 (2021-04-03 16:40), 0.6.0 (2021-05-30 06:30), 0.6.1 (2021-06-13 14:20), 0.7.0 (2021-07-16 09:40), 1.0.0 (2021-09-14 20:10), 1.1.0 (2021-10-18 18:20), 1.1.1 (2022-01-12 17:22), 1.2.0 (2022-04-07 21:42), 1.2.1 (2022-06-01 09:20), 1.2.2 (2022-06-07 23:50), 1.2.3 (2022-10-18 14:52), 1.2.4 (2022-11-16 13:10), 1.2.5 (2023-02-07 20:32), 1.2.6 (2023-03-31 14:10), 1.2.7 (2023-07-03 17:10), 1.2.8 (2023-09-02 17:10), 1.3.0 (2024-07-29 19:30)
Other packages that cited modeltime R package
View modeltime citation profile
Other R packages that modeltime depends, imports, suggests or enhances
Complete documentation for modeltime
Functions, R codes and Examples using the modeltime R package
Some associated functions: Adam_predict_impl . Arima_fit_impl . Arima_predict_impl . Auto_adam_predict_impl . adam_fit_impl . adam_params . adam_reg . add_modeltime_model . arima_boost . arima_params . arima_reg . arima_xgboost_fit_impl . arima_xgboost_predict_impl . auto_adam_fit_impl . auto_arima_fit_impl . auto_arima_xgboost_fit_impl . combine_modeltime_tables . control_modeltime . create_model_grid . create_xreg_recipe . croston_fit_impl . croston_predict_impl . dot_prepare_transform . drop_modeltime_model . ets_fit_impl . ets_predict_impl . exp_smoothing . exp_smoothing_params . get_arima_description . get_model_description . get_tbats_description . is_calibrated . is_modeltime_model . is_modeltime_table . is_residuals . load_namespace . log_extractors . m750 . m750_models . m750_splits . m750_training_resamples . maape . maape_vec . make_ts_splits . mdl_time_forecast . mdl_time_refit . metric_sets . modeltime_accuracy . modeltime_calibrate . modeltime_fit_workflowset . modeltime_forecast . modeltime_nested_fit . modeltime_nested_forecast . modeltime_nested_refit . modeltime_nested_select_best . modeltime_refit . modeltime_residuals . modeltime_residuals_test . modeltime_table . naive_fit_impl . naive_predict_impl . naive_reg . new_modeltime_bridge . nnetar_fit_impl . nnetar_params . nnetar_predict_impl . nnetar_reg . panel_tail . parallel_start . parse_index . pipe . plot_modeltime_forecast . plot_modeltime_residuals . pluck_modeltime_model . prep_nested . prophet_boost . prophet_fit_impl . prophet_params . prophet_predict_impl . prophet_reg . prophet_xgboost_fit_impl . prophet_xgboost_predict_impl . pull_modeltime_residuals . pull_parsnip_preprocessor . recipe_helpers . recursive . seasonal_reg . smooth_fit_impl . smooth_predict_impl . snaive_fit_impl . snaive_predict_impl . stlm_arima_fit_impl . stlm_arima_predict_impl . stlm_ets_fit_impl . stlm_ets_predict_impl . summarize_accuracy_metrics . table_modeltime_accuracy . tbats_fit_impl . tbats_predict_impl . temporal_hier_fit_impl . temporal_hier_predict_impl . temporal_hierarchy . temporal_hierarchy_params . theta_fit_impl . theta_predict_impl . tidyeval . time_series_params . type_sum.mdl_time_tbl . update_model_description . update_modeltime_model . window_function_fit_impl . window_function_predict_impl . window_reg . xgboost_impl . xgboost_predict . 
Some associated R codes: 00_global_variables.R . data.R . dev-constructor.R . dev-model_descriptions.R . dev-parse_index.R . dev-xregs.R . dials-adam_params.R . dials-arima_params.R . dials-ets_params.R . dials-nnetar_params.R . dials-prophet_params.R . dials-temporal_hierarchy_params.R . dials-ts_params.R . helpers-modeltime_residuals.R . helpers-modeltime_table.R . modeltime-accuracy-table.R . modeltime-accuracy.R . modeltime-calibrate.R . modeltime-fit-workflowset.R . modeltime-forecast-plot.R . modeltime-forecast.R . modeltime-recursive.R . modeltime-refit.R . modeltime-residuals-plot.R . modeltime-residuals-tests.R . modeltime-residuals.R . modeltime-table.R . nested-modeltime-forecast.R . nested-modeltime_data_prep.R . nested-modeltime_extractors.R . nested-modeltime_fit.R . nested-modeltime_refit.R . nested-modeltime_select_best.R . parsnip-adam.R . parsnip-adam_data.R . parsnip-arima_boost.R . parsnip-arima_boost_data.R . parsnip-arima_reg.R . parsnip-arima_reg_data.R . parsnip-exp_smoothing.R . parsnip-exp_smoothing_data.R . parsnip-naive_reg.R . parsnip-naive_reg_data.R . parsnip-nnetar_reg.R . parsnip-nnetar_reg_data.R . parsnip-prophet_boost.R . parsnip-prophet_boost_data.R . parsnip-prophet_reg.R . parsnip-prophet_reg_data.R . parsnip-seasonal_reg.R . parsnip-seasonal_reg_data.R . parsnip-temporal_hierarchy.R . parsnip-temporal_hierarchy_data.R . parsnip-window_reg.R . parsnip-window_reg_data.R . tibble-type_sum.R . utils-checks-validations.R . utils-control-par.R . utils-is_modeltime.R . utils-make_grouped_predictions.R . utils-parsnip-helpers.R . utils-pipe.R . utils-tidy-eval.R . utils-xgboost.R . yardstick-metric-sets.R . zzz.R .  Full modeltime package functions and examples
Downloads during the last 30 days
04/0704/0804/0904/1004/1104/1204/1304/1404/1504/1604/1704/1804/1904/2004/2104/2204/2304/2404/2504/2604/2704/2804/2904/3005/0105/0205/0305/0405/0505/06Downloads for modeltime30405060708090100110120130140150TrendBars

Today's Hot Picks in Authors and Packages

quickcode  
Quick and Essential 'R' Tricks for Better Scripts
The NOT functions, 'R' tricks and a compilation of some simple quick plus often used 'R' codes to im ...
Download / Learn more Package Citations See dependency  
humanize  
Create Values for Human Consumption
An almost direct port of the 'python' 'humanize' package . Thi ...
Download / Learn more Package Citations See dependency  
MLDS  
Maximum Likelihood Difference Scaling
Difference scaling is a method for scaling perceived supra-threshold differences. The package cont ...
Download / Learn more Package Citations See dependency  
aroma.affymetrix  
Analysis of Large Affymetrix Microarray Data Sets
A cross-platform R framework that facilitates processing of any number of Affymetrix microarray samp ...
Download / Learn more Package Citations See dependency  
funLBM  
Model-Based Co-Clustering of Functional Data
The funLBM algorithm allows to simultaneously cluster the rows and the columns of a data matrix wher ...
Download / Learn more Package Citations See dependency  

24,205

R Packages

207,311

Dependencies

65,312

Author Associations

24,206

Publication Badges

© Copyright since 2022. All right reserved, rpkg.net.  Based in Cambridge, Massachusetts, USA