Explain briefly the additive and multiplicative models of time series. Which of these models is more commonly used and why?

The additive and multiplicative models are two different approaches to decomposing a time series into its components. The choice between the two models depends on the characteristics of the data and the nature of the underlying patterns.

The Additive Model:
In the additive model, it is assumed that the time series can be represented as the sum of its components. The basic form of the additive model is:

Y(t) = T(t) + S(t) + C(t) + I(t)

Where:
- Y(t) is the observed time series value at time t
- T(t) is the trend component, representing the long-term pattern or overall direction of the series
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