Automatic Forecasting Procedure

add_changepoints_to_plot | Get layers to overlay significant changepoints on prophet... |

add_country_holidays | Add in built-in holidays for the specified country. |

add_group_component | Adds a component with given name that contains all of the... |

add_regressor | Add an additional regressor to be used for fitting and... |

add_seasonality | Add a seasonal component with specified period, number of... |

construct_holiday_dataframe | Construct a dataframe of holiday dates. |

coverage | Coverage |

cross_validation | Cross-validation for time series. |

df_for_plotting | Merge history and forecast for plotting. |

dyplot.prophet | Plot the prophet forecast. |

fit.prophet | Fit the prophet model. |

fourier_series | Provides Fourier series components with the specified... |

generate_cutoffs | Generate cutoff dates |

generated_holidays | holidays table |

get_holiday_names | Return all possible holiday names of given country |

initialize_scales_fn | Initialize model scales. |

linear_growth_init | Initialize linear growth. |

logistic_growth_init | Initialize logistic growth. |

mae | Mean absolute error |

make_all_seasonality_features | Dataframe with seasonality features. Includes seasonality... |

make_future_dataframe | Make dataframe with future dates for forecasting. |

make_holiday_features | Construct a matrix of holiday features. |

make_holidays_df | Make dataframe of holidays for given years and countries |

make_seasonality_features | Data frame with seasonality features. |

mape | Mean absolute percent error |

mse | Mean squared error |

parse_seasonality_args | Get number of Fourier components for built-in seasonalities. |

performance_metrics | Compute performance metrics from cross-validation results. |

piecewise_linear | Evaluate the piecewise linear function. |

piecewise_logistic | Evaluate the piecewise logistic function. |

plot_cross_validation_metric | Plot a performance metric vs. forecast horizon from cross... |

plot_forecast_component | Plot a particular component of the forecast. |

plot.prophet | Plot the prophet forecast. |

plot_seasonality | Plot a custom seasonal component. |

plot_weekly | Plot the weekly component of the forecast. |

plot_yearly | Plot the yearly component of the forecast. |

predictive_samples | Sample from the posterior predictive distribution. |

predict.prophet | Predict using the prophet model. |

predict_seasonal_components | Predict seasonality components, holidays, and added... |

predict_trend | Predict trend using the prophet model. |

predict_uncertainty | Prophet uncertainty intervals for yhat and trend |

prophet | Prophet forecaster. |

prophet_copy | Copy Prophet object. |

prophet_plot_components | Plot the components of a prophet forecast. Prints a ggplot2... |

regressor_column_matrix | Dataframe indicating which columns of the feature matrix... |

rmse | Root mean squared error |

rolling_mean_by_h | Compute a rolling mean of x, after first aggregating by h |

sample_model | Simulate observations from the extrapolated generative model. |

sample_posterior_predictive | Prophet posterior predictive samples. |

sample_predictive_trend | Simulate the trend using the extrapolated generative model. |

seasonality_plot_df | Prepare dataframe for plotting seasonal components. |

set_auto_seasonalities | Set seasonalities that were left on auto. |

set_changepoints | Set changepoints |

set_date | Convert date vector |

setup_dataframe | Prepare dataframe for fitting or predicting. |

time_diff | Time difference between datetimes |

validate_column_name | Validates the name of a seasonality, holiday, or regressor. |

validate_inputs | Validates the inputs to Prophet. |

Embedding an R snippet on your website

Add the following code to your website.

For more information on customizing the embed code, read Embedding Snippets.