prophesize: Facebook's Prophet Forecast

In lares: Analytics & Machine Learning Sidekick

Facebook's Prophet Forecast

Description

Prophet is Facebook's 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.

Usage

prophesize(
  df,
  n_future = 60,
  country = NULL,
  trend.param = 0.05,
  logged = FALSE,
  pout = 0.03,
  project = "Prophet Forecast"
)

Arguments

df	Data frame. Must contain date/time column and values column, in that order.
n_future	Integer. How many steps do you wish to forecast?
country	Character. Country code for holidays.
trend.param	Numeric. Flexibility of trend component. Default is 0.05, and as this value becomes larger, the trend component will be more flexible.
logged	Boolean. Convert values into logs?
pout	Numeric. Get rid of pout % of outliers.
project	Character. Name of your forecast project for plot title

Details

Official documentation: https://github.com/facebook/prophet

Value

List. Containing the forecast results, the prophet model, and a plot.

See Also

Other Forecast: forecast_arima()

lares documentation built on Sept. 13, 2024, 1:08 a.m.