total_approved_accounts_revenue ~ paid_search_clicks_lag_2_moving_average_2 + kwai_clicks_lag_2_moving_average_1 + fb_level_achieved_tier_2_clicks_lag_2_moving_average_2 + fb_level_achieved_tier_1_impressions_lag_2_moving_average_2 + ga_app_clicks_lag_2_moving_average_2 + digital_tactic_others_clicks_lag_1_moving_average_2 + programmatic_clicks_lag_1_moving_average_2

    Class to contain results of fitting a linear mixed effects model.

    MixedLMResults inherits from statsmodels.LikelihoodModelResults

    Parameters
    ----------
    See statsmodels.LikelihoodModelResults

    Attributes
    model : class instance
        Pointer to MixedLM model instance that called fit.
    normalized_cov_params : ndarray
        The sampling covariance matrix of the estimates
    params : ndarray
        A packed parameter vector for the profile parameterization.
        The first `k_fe` elements are the estimated fixed effects
        coefficients.  The remaining elements are the estimated
        variance parameters.  The variance parameters are all divided
        by `scale` and are not the variance parameters shown
        in the summary.
    fe_params : ndarray
        The fitted fixed-effects coefficients
    cov_re : ndarray
        The fitted random-effects covariance matrix
    bse_fe : ndarray
        The standard errors of the fitted fixed effects coefficients
    bse_re : ndarray
        The standard errors of the fitted random effects covariance
        matrix and variance components.  The first `k_re * (k_re + 1)`
        parameters are the standard errors for the lower triangle of
        `cov_re`, the remaining elements are the standard errors for
        the variance components.

    See Also
    --------
    statsmodels.LikelihoodModelResults