Question

我正在尝试使用Dickey Fuller Test检查我的时间序列是否静止。看看我的原始数据，我很确定它们不是静止的。但是，在使用python对我的数据实施Dickey Fuller测试后，结果显示我的时间序列是静止的（具有非常低的p值）。

我的代码和结果如下：

def test_stationarity(timeseries):

    #Determing rolling statistics
    rolmean = timeseries.rolling(window=7,center=False).mean()
    rolstd = timeseries.rolling(window=7,center=False).std()

    #Plot rolling statistics:
    orig = plt.plot(timeseries, color='blue',label='Original')
    mean = plt.plot(rolmean, color='red', label='Rolling Mean')
    std = plt.plot(rolstd, color='black', label = 'Rolling Std')
    plt.legend(loc='best')
    plt.title('Rolling Mean & Standard Deviation')
    #plt.savefig('stationarity_{}.png'.format(timeseries.columns.values[0]))
    #plt.show(block=False)

    #Perform Dickey-Fuller test:
    print ('Results of Dickey-Fuller Test:')
    dftest = adfuller(timeseries.values.ravel(), autolag='AIC')
    dfoutput = pd.Series(dftest[0:4], index=['Test Statistic','p-value','#Lags Used','Number of Observations Used'])
    for key,value in dftest[4].items():
        dfoutput['Critical Value (%s)'%key] = value
    print (dfoutput)

The data is a timesries of physical cross-border electricity flow between Germany and France in hourly time-frame. Negative values indicate electricity flow from Germany to France

Results of Dickey-Fuller Test:
Test Statistic                -7.252678e+00
p-value                        1.763304e-10
Lags Used                      4.600000e+01
Number of Observations Used    2.031600e+04
Critical Value (1%)           -3.430672e+00
Critical Value (5%)           -2.861682e+00
Critical Value (10%)          -2.566846e+00

有人可以解释一下这怎么可能？是否有任何使用Dickey Fuller测试的假设？

Dickey Fuller测试显示显着性但平均值不是恒定的

0 个答案: