python statsmodel的使用

import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import statsmodels.api as sm
from statsmodels.graphics.tsaplots import acf, pacf, plot_acf, plot_pacf
from statsmodels.tsa.arima_model import ARMA
from statsmodels.tsa.stattools import arma_order_select_ic

if __name__ == "__main__":

  time_series = pd.Series(
    [151.0, 188.46, 199.38, 219.75, 241.55, 262.58, 328.22, 396.26, 442.04, 517.77, 626.52, 717.08, 824.38, 913.38,
     1088.39, 1325.83, 1700.92, 2109.38, 2499.77, 2856.47, 3114.02, 3229.29, 3545.39, 3880.53, 4212.82, 4757.45,
     5633.24, 6590.19, 7617.47, 9333.4, 11328.92, 12961.1, 15967.61])
  # print('BIC求解的模型阶次为', arma_order_select_ic(time_series, max_ar=10, max_ma=6, ic='bic')['bic_min_order'])
  print('time_series:', len(time_series))
  my_arma = ARMA(time_series, (1, 0)) # 这里的(1, 0)从arma_order_select_ic函数返回,但是这里返回6,7运行失败
  model = my_arma.fit()
  result = model.forecast(10)[0]
  print('result:', result)