def predict(self,x):
        self.xpredict = x
        distxpredict = self.kernel(x, self.x, scale=self.scale)
        self.ypredict = np.dot(distxpredict, self.parest)
        return self.ypredict
predict new y values for a given array of explanatory variables
dataset/ETHPy150Open statsmodels/statsmodels/statsmodels/sandbox/regression/kernridgeregress_class.py/GaussProcess.predict