Time Series Decomposition
Overview
The classical time series decomposition model, models a time series as a sum of a trend, seasonal factors, and a
random noise term.
{% y_t = trend_t + seasonlity_t + \epsilon_t %}
Seasonality
Sometimes a time series shows seasonal patterns, that is, there is a periodic component to it.
{% Y_t = S_t + X_t %}
where S is a peridic function.
