def get_model()

in pplbench/ppls/pymc3/robust_regression.py [0:0]

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

    def get_model(self, data: xr.Dataset) -> pm.Model:
        # transpose the dataset to ensure that it is the way we expect
        data = data.transpose("item", "feature")

        with pm.Model() as model:
            X = pm.Data("x_obs", data.X.values)
            Y = pm.Data("y_obs", data.Y.values)

            alpha = pm.Normal("alpha", mu=0, sd=self.alpha_scale)
            beta = pm.Normal("beta", mu=self.beta_loc, sd=self.beta_scale, shape=self.k)
            nu = pm.Gamma("nu", alpha=2, beta=0.1)
            sigma = pm.Exponential("sigma", lam=1 / self.sigma_mean)
            mu = alpha + X.dot(beta)
            pm.StudentT("Y", nu=nu, mu=mu, sigma=sigma, observed=Y, shape=self.n)

        return model