时间序列中，用bic准则时出现一整个数组

import pandas as pd
import matplotlib.pyplot as plt

import itertools
import numpy as np
import seaborn as sns
ChinaBank = pd.read_csv('ChinaBank.csv',index_col = 'Date',parse_dates=['Date'])

#ChinaBank.index = pd.to_datetime(ChinaBank.index)
sub = ChinaBank['2014-01':'2014-06']['Close']
train = sub.loc['2014-01':'2014-03']
test = sub.loc['2014-04':'2014-06']
plt.figure(figsize=(10,10))
print(train)
plt.plot(train)
plt.show()
ChinaBank['Close_diff_1'] = ChinaBank['Close'].diff(1)
ChinaBank['Close_diff_2'] = ChinaBank['Close_diff_1'].diff(1)
fig = plt.figure(figsize=(20,6))
ax1 = fig.add_subplot(131)
ax1.plot(ChinaBank['Close'])
ax2 = fig.add_subplot(132)
ax2.plot(ChinaBank['Close_diff_1'])
ax3 = fig.add_subplot(133)
ax3.plot(ChinaBank['Close_diff_2'])
plt.show()

#遍历，寻找适宜的参数
p_min = 0
d_min = 0
q_min = 0
p_max = 5
d_max = 5
q_max = 5

# Initialize a DataFrame to store the results,，以BIC准则
results_bic = pd.DataFrame(index=['AR{}'.format(i) for i in range(p_min, p_max + 1)],
                           columns=['MA{}'.format(i) for i in range(q_min, q_max + 1)])

for p, d, q in itertools.product(range(p_min, p_max + 1),
                                 range(d_min, d_max + 1),
                                 range(q_min, q_max + 1)):
        if p == 0 and d == 0 and q == 0:
            results_bic.loc['AR{}'.format(p), 'MA{}'.format(q)] = np.nan
            continue

        try:
            model = sm.tsa.ARIMA(train, order=(p, d, q),
                                 # enforce_stationarity=False,
                                 # enforce_invertibility=False,
                                 )
            results = model.fit()
            results_bic.loc['AR{}'.format(p), 'MA{}'.format(q)] = results.bic
        except:
            continue

results_bic = results_bic[results_bic.columns].astype(float)
print(results_bic)
fig, ax = plt.subplots(figsize=(10, 8))
ax = sns.heatmap(results_bic,
                 mask=results_bic.isnull(),
                 ax=ax,
                 annot=True,
                 fmt='.2f',
                 )
ax.set_title('BIC')
plt.show()

数据在网盘中：
http://pan.baidu.com/s/1gfxRFbH
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