arch.univariate.HARX.fit¶
-
HARX.
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 Bollerslev-Wooldridge 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 model-specific non-linear 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.