Time series are series of data points listed in time order. Time series forecasting is the use of a model to predict future values based on previously observed values.
Uses a number of lagged observations of time series to forecast observations Inputs / Parameters:
- p: the number of lag observations in the model; also known as the lag order (AR)
- d: the number of times that the raw observations are differenced; also known as the degree of differencing (I)
- q: the size of the moving average window; also known as the order of the moving average (MA)
Prophet is open source software released by Facebook’s Core Data Science team Prophet is a procedure for forecasting time series data based on an additive model where non-linear trends are fit with yearly, weekly, and daily seasonality 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.