arch.univariate.ZeroMean.fit¶

ZeroMean.
fit
(update_freq=1, disp='final', starting_values=None, cov_type='robust', show_warning=True, first_obs=None, last_obs=None, tol=None, options=None, backcast=None)¶ Fits the model given a nobs by 1 vector of sigma2 values
 Parameters
update_freq (int, optional) – Frequency of iteration updates. Output is generated every update_freq iterations. Set to 0 to disable iterative output.
disp (str) – Either ‘final’ to print optimization result or ‘off’ to display nothing
starting_values (ndarray, optional) – Array of starting values to use. If not provided, starting values are constructed by the model components.
cov_type (str, optional) – Estimation method of parameter covariance. Supported options are ‘robust’, which does not assume the Information Matrix Equality holds and ‘classic’ which does. In the ARCH literature, ‘robust’ corresponds to BollerslevWooldridge covariance estimator.
show_warning (bool, optional) – Flag indicating whether convergence warnings should be shown.
first_obs ({int, str, datetime, Timestamp}) – First observation to use when estimating model
last_obs ({int, str, datetime, Timestamp}) – Last observation to use when estimating model
tol (float, optional) – Tolerance for termination.
options (dict, optional) – Options to pass to scipy.optimize.minimize. Valid entries include ‘ftol’, ‘eps’, ‘disp’, and ‘maxiter’.
backcast (float, optional) – Value to use as backcast. Should be measure \(\sigma^2_0\) since modelspecific nonlinear transformations are applied to value before computing the variance recursions.
 Returns
results – Object containing model results
 Return type
Notes
A ConvergenceWarning is raised if SciPy’s optimizer indicates difficulty finding the optimum.
Parameters are optimized using SLSQP.