statsmodels.tsa.innovations.arma_innovations.arma_innovations#
- statsmodels.tsa.innovations.arma_innovations.arma_innovations(endog, ar_params=None, ma_params=None, sigma2=1, normalize=False, prefix=None)[source]#
Compute innovations using a given ARMA process
- Parameters:
- endog
ndarray The observed time-series process, may be univariate or multivariate.
- ar_params
ndarray,optional Autoregressive parameters.
- ma_params
ndarray,optional Moving average parameters.
- sigma2
ndarray,optional The ARMA innovation variance. Default is 1.
- normalizebool,
optional Whether or not to normalize the returned innovations. Default is False.
- prefix
str,optional The BLAS prefix associated with the datatype. Default is to find the best datatype based on given input. This argument is typically only used internally.
- endog
- Returns:
- innovations
ndarray Innovations (one-step-ahead prediction errors) for the given endog series with predictions based on the given ARMA process. If normalize=True, then the returned innovations have been “whitened” by dividing through by the square root of the mean square error.
- innovations_mse
ndarray Mean square error for the innovations.
- innovations