arch.univariate.ARX.fit¶
-
ARX.fit(update_freq: int =
1
, disp: bool | 'off' | 'final' ='final'
, starting_values: ndarray | Series | None =None
, cov_type: 'robust' | 'classic' ='robust'
, show_warning: bool =True
, first_obs: int | str | datetime | datetime64 | Timestamp | None =None
, last_obs: int | str | datetime | datetime64 | Timestamp | None =None
, tol: float | None =None
, options: dict[str, Any] | None =None
, backcast: None | float | ndarray =None
) ARCHModelResult ¶ Estimate model parameters
- Parameters:¶
- update_freq: int =
1
¶ Frequency of iteration updates. Output is generated every update_freq iterations. Set to 0 to disable iterative output.
- disp: bool | 'off' | 'final' =
'final'
¶ Either ‘final’ to print optimization result or ‘off’ to display nothing. If using a boolean, False is “off” and True is “final”
- starting_values: ndarray | Series | None =
None
¶ Array of starting values to use. If not provided, starting values are constructed by the model components.
- cov_type: 'robust' | 'classic' =
'robust'
¶ 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 =
True
¶ Flag indicating whether convergence warnings should be shown.
- first_obs: int | str | datetime | datetime64 | Timestamp | None =
None
¶ First observation to use when estimating model
- last_obs: int | str | datetime | datetime64 | Timestamp | None =
None
¶ Last observation to use when estimating model
- tol: float | None =
None
¶ Tolerance for termination.
- options: dict[str, Any] | None =
None
¶ Options to pass to scipy.optimize.minimize. Valid entries include ‘ftol’, ‘eps’, ‘disp’, and ‘maxiter’.
- backcast: None | float | ndarray =
None
¶ 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.
- update_freq: int =
- Returns:¶
results – Object containing model results
- Return type:¶
ARCHModelResult
Notes
A ConvergenceWarning is raised if SciPy’s optimizer indicates difficulty finding the optimum.
Parameters are optimized using SLSQP.