Practicing repo for learning different forecasting methods.
- Data source: Stats Canada - Producer deliveries of major grains
- Reference repo: TS forecasting with Python by @jiwidi
- Time series decomposition
- Level
- Trend
- Seasonality
- Noise
- Stationarity
- AC and PAC plots
- Rolling mean and std
- Dickey-Fuller test
- Making our time series stationary
- Difference transform
- Log scale
- Smoothing
- Moving average
- Autoregression (AR)
- Moving Average (MA)
- Autoregressive Moving Average (ARMA)
- Autoregressive integraded moving average (ARIMA)
- Seasonal autoregressive integrated moving average (SARIMA)
- Bayesian regression Link
- Lasso Link
- SVM Link
- Randomforest Link
- Nearest neighbors Link
- XGBoost Link
- Lightgbm Link
- Prophet Link
- Long short-term memory with tensorflow (LSTM)Link
- DeepAR
WIP