A widely used model for time series forecasting that incorporates autoregressive, moving average,
and differencing components.

Seasonal ARIMA model that captures both trend and seasonal patterns in time series data
for accurate predictions.

Robust model developed by Facebook for time series forecasting with built-in flexibility
and automatic trend detection.

Long Short-Term Memory model, a type of recurrent neural network known for effectively capturing
long-term dependencies in sequential data.

Gated Recurrent Unit, a variant of LSTM that offers similar benefits, including the ability to model
long-range dependencies in time series

Vector Autoregression model used for multivariate time series forecasting, capturing the relationships among
multiple variables.