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prophet (version 0.1)

Automatic Forecasting Procedure

Description

Implements a procedure for forecasting time series data based on an additive model where non-linear trends are fit with yearly and weekly seasonality, plus holidays. It works best with daily periodicity data with at least one year of historical data. Prophet is robust to missing data, shifts in the trend, and large outliers.

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Version

Install

install.packages('prophet')

Monthly Downloads

11,972

Version

0.1

License

BSD_3_clause + file LICENSE

Maintainer

Sean Taylor

Last Published

February 1st, 2017

Functions in prophet (0.1)

get_changepoint_times

Gets changepoint times, in scaled space.
make_all_seasonality_features

Data frame 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.
predict_trend

Predict trend using the prophet model.
predict.prophet

Predict using the prophet model.
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.
predict_uncertainty

Prophet uncertainty intervals.
sample_predictive_trend

Simulate the trend using the extrapolated generative model.
predict_seasonal_components

Seasonality broken down into components
plot.prophet

Plot the prophet forecast.
set_changepoints

Set changepoints
piecewise_linear

Evaluate the piecewise linear function.
piecewise_logistic

Evaluate the piecewise logistic function.
setup_dataframe

Prepare dataframe for fitting or predicting.
validate_inputs

Validates the inputs to Prophet.
sample_model

Simulate observations from the extrapolated generative model.
prophet

Prophet forecast.
get_changepoint_matrix

Gets changepoint matrix for history dataframe.
get_changepoint_indexes

Gets changepoint indexes in history dataframe.
linear_growth_init

Initialize linear growth
compile_stan_model

Compile Stan model
fit.prophet

Fit the prophet model.
df_for_plotting

Merge history and forecast for plotting.
get_prophet_stan_model

Load Stan model
fourier_series

Provides fourier series components with the specified frequency.
logistic_growth_init

Initialize logistic growth