Python进行ARMA模型建模_arma模型python代码

import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
import statsmodels.api as sm
from statsmodels.tsa.arima.model import ARIMA
 
sns.set_theme()# 设置风格
%config InlineBackend.figure_format = 'retina' # 让图片更清晰
 
df = pd.read_excel('D:/data/HOUSTNSA.xlsx')# 导入数据
print(df)
 
data = df['HOUSTNSA'].values
year = pd.date_range("1/1/1959", periods=770, freq="M")
ts = pd.DataFrame(data, index=year,columns=['HOUSTNSA'])
 
print(ts)
 
res = sm.tsa.arma_order_select_ic(
    ts, 
    max_ar=2, 
    max_ma=2,ic=["aic", "bic"]
)# 定阶
res

{'aic': 0 1 2

0 7778.111863 7089.007586 6790.807042

1 6500.479592 6470.421294 6442.842546

2 6461.160567 6460.092841 6441.241159,

'bic': 0 1 2

0 7787.404644 7102.946758 6809.392604

1 6514.418764 6489.006857 6466.074499

2 6479.746129 6483.324793 6469.119502,

'aic_min_order': (2, 2),

'bic_min_order': (1, 2)}

mod = ARIMA(ts,order=(2, 0, 2))
res = mod.fit()
print(res.summary())# 拟合模型

fig = plt.figure(figsize=(16, 9))
fig = res.plot_diagnostics(fig=fig, lags=30)
plt.savefig("tsplot2.png", dpi = 600, bbox_inches = 'tight')
plt.show()