📄️ ARIMA
ARIMA (AutoRegressive Integrated Moving Average) is a popular time series forecasting model that combines autoregressive (AR), differencing (I), and moving average (MA) components to capture the patterns and dependencies in time series data. It is widely used for analyzing and forecasting time-dependent data points.
📄️ Auto ARIMA
Auto ARIMA, short for Automated ARIMA, is a variation of the ARIMA model that automates the selection of the order parameters (p, d, q) for the ARIMA model. It uses a stepwise algorithm to automatically determine the optimal values for these parameters based on the characteristics of the time series data.
📄️ Theta
The Theta model is a forecasting technique that combines a simple exponential smoothing approach with a linear trend component. It is useful for forecasting time series data that exhibits a linear trend.