def fit()

in svinfer/linear_model/linear_regression.py [0:0]

• 18 lines of code
• 1 McCabe index (conditional complexity)

    def fit(self, data):
        """
        fit model
        :return: a tuple; the 1st element is the estimated beta,
        the 2nd element is the estimated sigma squared, the 3rd element is
        the estimated variance-covariance matrix of the estimated beta.
        """
        n, xtx, xty, yty = self._preprocess_data(data)
        self.beta, self.sigma_sq, omega = LinearRegressionCoefficients(
            n, xtx, xty, yty, self.x_s2, df_corrected=self.df_corrected
        ).estimate_all()

        self.beta_vcov = LinearRegressionVariance(
            n,
            xtx,
            xty,
            yty,
            self.sigma_sq,
            omega,
            self.x_s2,
            n_replications=self.n_replications,
            random_state=self.random_state,
        ).simulate_beta_vcov()

        self.beta_standarderror = np.sqrt(np.diag(self.beta_vcov))
        return self