I've fitted Prophet with logistic growth and multiplicative seasonality over time series data (daily observations spanning several years, no additional regressors; just ds, y) and have the forecast dataframe. How do I use the values from forecast to remove seasonality?
Within forecast, I acknowledge the weekly and yearly columns deal with seasonality on a weekly/yearly basis, and multiplicative_terms deals with changing magnitudes over time; but I don't know how to put this together to remove seasonality form my data.
I have the following possibly ways about attempting to remove seasonality, but believe what I'm doing is wrong.
#R
df$y - forecast$trend * forecast$multiplicative_terms * forecast$weekly * forecast$yearly
For reference, when using seasonal_decompose, I've had to use the following to get rid of seasonality; this doesn't hold for Prophet because of the additional terms.
#Python
df.y - trend* decomposition.seasonal
Edit- After doing a bit of research, I'm currently running this which looks right, but I was wondering if anyone can confirm whether this is the correct way to remove seasonality + trend?
df$y -
(forecast$trend +
(forecast$trend * forecast$weekly) +
(forecast$trend * forecast$yearly) +
(forecast$trend * forecast$multiplicative_terms)
)