Standard Errors assume that the covariance matrix of the errors is correctly specified.


    Results class for for an OLS model.

    Parameters
    ----------
    model : RegressionModel
        The regression model instance.
    params : ndarray
        The estimated parameters.
    normalized_cov_params : ndarray
        The normalized covariance parameters.
    scale : float
        The estimated scale of the residuals.
    cov_type : str
        The covariance estimator used in the results.
    cov_kwds : dict
        Additional keywords used in the covariance specification.
    use_t : bool
        Flag indicating to use the Student's t in inference.
    **kwargs
        Additional keyword arguments used to initialize the results.

    See Also
    --------
    RegressionResults
        Results store for WLS and GLW models.

    Notes
    -----
    Most of the methods and attributes are inherited from RegressionResults.
    The special methods that are only available for OLS are:

    - get_influence
    - outlier_test
    - el_test
    - conf_int_el
    