python statsmodels：用于预测arima模型功能的“params”参数

Question

ARIMA ( statsmodels.tsa.arima_model.ARIMA ), AR ( statsmodels.tsa.ar_model.AR ), and ARMA ( statsmodels.tsa.arima_model.ARMA ) in statsmodels all take in the parameters of their model in their predict method. For example, for the AR object, we have the following function definitions:

• AR(endog, dates=None, freq=None, missing='none')[source]
• fit([maxlag, method, ic, trend, ...])
• predict(params[, start, end, dynamic])

( Link to documentation here )

I'm actually very confused about the parameter choices for predict . predict 's first parameter is the parameters to the constructor of AR ; it doesn't make sense that these once again appear in the parameter for predict . They also appear for the constructors for ARIMA and ARMA . Can someone answer why this parameter exists?

For what its worth, I don't have much background in time series analysis, so perhaps there is some functionality that is exposed when reusing parameters. Otherwise, this parameter is a nuisance.

Answer 1

I answered your question on the issue tracker here . You want to call predict on the results object returned from fit. This the pattern that we follow.

model = sm.tsa.ARMA(y, (2, 2))
results = model.fit()
results.predict()