Time Series Classical Decomposition

This component aims to decompose a Time Series using the Classical Decomposition approach. The component has both a visual and data output that produces the following elements:
- Detrended Time Series
- Deseasonalized Time Series
- Seasonal Factors
- Fitted Time Series
- Error component

Either the method with Additive Seasonality or the method with Multiplicative Seasonality can be selected. Moreover you can select between two trend estimation methods (Centered Moving Average and Polynomial Curve FItting)

Input ports

1. Type: Table
   Time Series Data
   Insert Time Series Data (please SORT your Time Series in advance in order to keep the temporal sequence of the data)

Output ports

1. Type: Table
   Time Series Decomposition
   Decomposition columns (Estimated Trend, Detrended Series, Seasonal Factors, Deseasonalized Series, Errors, Fitted Series) plus original columns