Modeling Seasonality

Time-series data typically exhibit a seasonality component, which can be modeled in various ways. Assuming we are using a linear regression model, the simplest approach is to include indicator variables for each month. This method makes the coefficients easy to interpret, but the resulting pattern is not smooth. Alternatively, Fourier terms can produce a smooth seasonal curve, though their coefficients are harder to interpret. Periodic splines offer the best of both worlds; providing smoothness while retaining interpretability.