Different algorithms for time-series modeling/forecasting

• Autoregression (AR)
• Moving Average (MA)
• Autoregressive Moving Average (ARMA)
• Autoregressive Integrated Moving Average (ARIMA)
• Seasonal Autoregressive Integrated Moving-Average (SARIMA)
• Seasonal Autoregressive Integrated Moving-Average with Exogenous Regressors (SARIMAX)
• Vector Autoregression (VAR)
• Vector Autoregression Moving-Average (VARMA)
• Vector Autoregression Moving-Average with Exogenous Regressors (VARMAX)
• Simple Exponential Smoothing (SES)
• Holt Winter’s Exponential Smoothing (HWES)

Other algorithms for time-series forecasting are-

• Multi-Layer Perceptron (MLP)
• Bayesian Neural Network (BNN)
• Radial Basis Functions (RBF)
• Generalized Regression Neural Networks (GRNN), also called kernel regression
• K-Nearest Neighbor regression (KNN)
• CART regression trees (CART)
• Support Vector Regression (SVR)
• Gaussian Processes (GP)
• Recurrent Neural Network (RNN)
• Long Short-Term Memory (LSTM)

End-to-end Time-series Modeling

Python Library	Details
Darts	GitHub Documentation
nixtla	GitHub API Reference

References:

• Darts’ Swiss Knife for Time Series Forecasting