883cee17114c35a597351b7cc0f1b7e040352d54,statsmodels/tsa/tests/test_holtwinters.py,TestHoltWinters,test_simulate,#TestHoltWinters#,728

Before Change

        // sim <- simulate(fit, innov = innov*fit$sigma)
        expected = [78.06170, 49.01698, 61.71652, 67.60118]

        fit = ExponentialSmoothing(
            self.austourists, seasonal_periods=4, trend="add", seasonal="mul"
        ).fit(
            smoothing_level=0.3156, smoothing_slope=1e-4, smoothing_seasonal=1e-4,
            // optimized=False
            // use_basinhopping=True
        )

        print(fit.summary())

        np.random.seed(0)

After Change

        np.random.seed(0)
        nsim = 100
        steps = 20
        sim = fit.simulate(steps, nsim=nsim, error="mul")

        import matplotlib.pyplot as plt
        n = len(self.austourists)
        plt.figure(figsize=(9, 6), dpi=100)
        plt.plot(range(n), self.austourists)
        plt.plot(range(n), fit.fittedvalues, "--")
        for i in range(nsim):
            plt.plot(range(n, n+steps), sim[:,i], "m-", alpha=0.1)
        plt.plot(range(n, n+4), expected)
        plt.grid()
        plt.savefig("test.png")

Instances