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I noted the existence of the function fit_trend that returns a regressor matrix and polynomial coefficients of some pre-specified order n. I was wondering if a similar function existed to fit for seasonality? When using the analyze function, how are the periodic signals extracted?
Best,
Kevin
The text was updated successfully, but these errors were encountered:
What do you exactly mean by that? I guess my question was not specific enough: I recall that when running analyze a Matrix was returned with points belonging to the seasonal component extracted from the original signal passed into analyze. I understand the autoregressive models capture these but is there a way within your framework to extract the parametric values that yield these seasonal components so that one could potentially manipulate these and/or plot seasonal components several forecasting steps ahead?
mutable struct PredictionData
trend_parameters
trend_regressor
seasonal_models
seasonal_predictions
end
the seasonal_models contain AR models from which you can get the parameters using the function ControlSystemsBase.denvec. The AR models themselves are transfer functions from ControlSystemsBase and they are estimated using ControlSystemIdentification.jl.
Hello,
I noted the existence of the function
fit_trend
that returns a regressor matrix and polynomial coefficients of some pre-specified order n. I was wondering if a similar function existed to fit for seasonality? When using theanalyze
function, how are the periodic signals extracted?Best,
Kevin
The text was updated successfully, but these errors were encountered: