Automatic Forecasting Procedure

Documentation for package ‘prophet’ version 0.1.1

Help Pages

compile_stan_model	Compile Stan model
df_for_plotting	Merge history and forecast for plotting.
fit.prophet	Fit the prophet model.
fourier_series	Provides Fourier series components with the specified frequency and order.
get_changepoint_matrix	Gets changepoint matrix for history dataframe.
get_prophet_stan_model	Load compiled Stan model
linear_growth_init	Initialize linear growth.
logistic_growth_init	Initialize logistic growth.
make_all_seasonality_features	Dataframe with seasonality features.
make_future_dataframe	Make dataframe with future dates for forecasting.
make_holiday_features	Construct a matrix of holiday features.
make_seasonality_features	Data frame with seasonality features.
piecewise_linear	Evaluate the piecewise linear function.
piecewise_logistic	Evaluate the piecewise logistic function.
plot.prophet	Plot the prophet forecast.
plot_holidays	Plot the holidays component of the forecast.
plot_trend	Plot the prophet trend.
plot_weekly	Plot the weekly component of the forecast.
plot_yearly	Plot the yearly component of the forecast.
predict.prophet	Predict using the prophet model.
predict_seasonal_components	Predict seasonality broken down into components.
predict_trend	Predict trend using the prophet model.
predict_uncertainty	Prophet uncertainty intervals.
prophet	Prophet forecaster.
prophet_plot_components	Plot the components of a prophet forecast. Prints a ggplot2 with panels for trend, weekly and yearly seasonalities if present, and holidays if present.
sample_model	Simulate observations from the extrapolated generative model.
sample_predictive_trend	Simulate the trend using the extrapolated generative model.
setup_dataframe	Prepare dataframe for fitting or predicting.
set_auto_seasonalities	Set seasonalities that were left on auto.
set_changepoints	Set changepoints
validate_inputs	Validates the inputs to Prophet.