statsmodels.tsa.stattools.innovations_filter¶
-
statsmodels.tsa.stattools.
innovations_filter
(endog, theta)¶ Filter observations using the innovations algorithm.
Parameters: endog : array_like
The time series to filter (nobs,). Should be demeaned if not mean 0.
theta : ndarray
Innovation coefficients of MA representation. Array must be (nobs, q) where q order of the MA.
Returns: ndarray
Array of filtered innovations.
See also
innovations_algo
- Convert autocovariances to MA parameters.
References
[*] Brockwell, P.J. and Davis, R.A., 2016. Introduction to time series and forecasting. Springer. Examples
>>> import statsmodels.api as sm >>> data = sm.datasets.macrodata.load_pandas() >>> rgdpg = data.data['realgdp'].pct_change().dropna() >>> acov = sm.tsa.acovf(rgdpg) >>> nobs = activity.shape[0] >>> theta, sigma2 = innovations_algo(acov[:4], nobs=nobs) >>> resid = innovations_filter(rgdpg, theta)