

def predict(self, x):
    'predict new y values for a given array of explanatory variables'
    self.xpredict = x
    distxpredict = self.kernel(x, self.x, scale=self.scale)
    self.ypredict = np.dot(distxpredict, self.parest)
    return self.ypredict

dataset/ETHPy150Open statsmodels/statsmodels/statsmodels/sandbox/regression/kernridgeregress_class.py GaussProcess.predict/original