# linearmodels.panel.results.PanelEffectsResults.f_statistic_robust¶

property PanelEffectsResults.f_statistic_robust: WaldTestStatistic

Joint test of significance for non-constant regressors

Returns
WaldTestStatistic

Statistic value, distribution and p-value

Notes

Implemented as a Wald test using the estimated parameter covariance, and so inherits any robustness that the choice of covariance estimator provides.

$W = \hat{\beta}_{-}' \hat{\Sigma}_{-}^{-1} \hat{\beta}_{-}$

where $$\hat{\beta}_{-}$$ does not include the model constant and $$\hat{\Sigma}_{-}$$ is the estimated covariance of the parameters, also excluding the constant. The test statistic is distributed as $$\chi^2_{k}$$ where k is the number of non- constant parameters.

If debiased is True, then the Wald statistic is divided by the number of restrictions and inference is made using an $$F_{k,df}$$ distribution where df is the residual degree of freedom from the model.

Return type

WaldTestStatistic