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prophet  

Automatic Forecasting Procedure
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("prophet", "1.1.7")



Attach the package and use:
library("prophet")
Maintained by
Sean Taylor
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2017-02-01
Latest Update: 2021-03-30
Description:
Implements a procedure for forecasting time series data based on an additive model where non-linear trends are fit with yearly, weekly, and daily seasonality, plus holiday effects. It works best with time series that have strong seasonal effects and several seasons of historical data. Prophet is robust to missing data and shifts in the trend, and typically handles outliers well.
How to cite:
Sean Taylor (2017). prophet: Automatic Forecasting Procedure. R package version 1.1.7, https://cran.r-project.org/web/packages/prophet. Accessed 08 Oct. 2026.
Previous versions and publish date:
(2026-07-09 06:44), 0.1.1 (2017-04-19 10:47), 0.1 (2017-02-01 08:34), 0.2.1 (2017-11-08 23:39), 0.2 (2017-09-12 09:48), 0.3.0.1 (2018-06-15 09:27), 0.3 (2018-06-02 06:58), 0.4 (2018-12-21 15:40), 0.5 (2019-05-14 23:50), 0.6.1 (2020-04-29 19:30), 0.6 (2020-03-03 10:20), 1.0 (2021-03-30 14:10)
Other packages that cited prophet R package
View prophet citation profile
Other R packages that prophet depends, imports, suggests or enhances
Complete documentation for prophet
Functions, R codes and Examples using the prophet R package
Some associated functions: add_changepoints_to_plot . add_country_holidays . add_group_component . add_regressor . add_seasonality . construct_holiday_dataframe . coverage . cross_validation . df_for_plotting . dyplot.prophet . fit.prophet . flat_growth_init . flat_trend . fourier_series . generate_cutoffs . generated_holidays . get_holiday_names . initialize_scales_fn . linear_growth_init . logistic_growth_init . mae . make_all_seasonality_features . make_future_dataframe . make_holiday_features . make_holidays_df . make_seasonality_features . mape . mdape . mse . parse_seasonality_args . performance_metrics . piecewise_linear . piecewise_logistic . plot.prophet . plot_cross_validation_metric . plot_forecast_component . plot_seasonality . plot_weekly . plot_yearly . predict.prophet . predict_seasonal_components . predict_trend . predict_uncertainty . predictive_samples . prophet . prophet_copy . prophet_plot_components . regressor_coefficients . regressor_column_matrix . rmse . rolling_mean_by_h . rolling_median_by_h . sample_model . sample_posterior_predictive . sample_predictive_trend . seasonality_plot_df . set_auto_seasonalities . set_changepoints . set_date . setup_dataframe . single_cutoff_forecast . smape . time_diff . validate_column_name . validate_inputs . 
Some associated R codes: data.R . diagnostics.R . make_holidays.R . plot.R . prophet.R . stanmodels.R . utilities.R . zzz.R .  Full prophet package functions and examples
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