Data Science, Timeseries, Time Series Analysis, Arima Model, Forecasting.
the time series from the decomposition approx = pywt.upcoef('a', coeffs[-1], 'db4', level=3, take=n) # Use ARIMA modeling to capture patterns in the reconstructed data # You can use other time series algorithms model = ARIMA(approx, order=(5,1,0)) model_fit = model.fit() # Forecast future values