Python autoarima参数选择过程-ARIMA/SARIMAX

Python autoarima参数选择过程-ARIMA/SARIMAX,python,forecasting,arima,grid-search,pmdarima,Python,Forecasting,Arima,Grid Search,Pmdarima,是否有任何方法可以阻止auto_arima函数达到产生无限aic的组合。我使用的是逐步搜索,不可能使用最大顺序作为参数。这是我的密码 from pmdarima.arima import ndiffs,nsdiffs test_df = grouped_df.get_group(items[k]) X = test_df['Quantity'].values train, test = X[0:len(X)-1], X[len(X)-1:] try: nsdiffs_D =

是否有任何方法可以阻止auto_arima函数达到产生无限aic的组合。我使用的是逐步搜索,不可能使用最大顺序作为参数。这是我的密码

 from pmdarima.arima import ndiffs,nsdiffs
 test_df = grouped_df.get_group(items[k])
 X = test_df['Quantity'].values
 train, test = X[0:len(X)-1], X[len(X)-1:]

 try:
     nsdiffs_D = nsdiffs(X,m=52)
     ndiffs_d = ndiffs(X,alpha=0.05)
     stepwise_fit = auto_arima(train, start_p=0, start_q=0,
                           max_p=6, max_q=6,m=52,
                           start_P=0,seasonal=True,alpha=0.05,
                           d=ndiffs_d,D=nsdiffs_D,trace=True,n_jobs=-1,
                           error_action='ignore',stepwise=True,suppress_warnings=True)
在参数搜索中,大多数给出无限AIC的组合都是花费太多时间的组合。我正在对2000多个产品进行网格搜索,当auto arima对其中许多产品花费太多时间时,这是没有用的。关于如何加快网格搜索过程,有什么建议吗。这里是一个网格搜索的输出

ARIMA(0,1,0)(0,0,1)[52] intercept   : AIC=1699.129, Time=2.52 sec
ARIMA(0,1,0)(0,0,0)[52] intercept   : AIC=1701.752, Time=0.02 sec
ARIMA(1,1,0)(1,0,0)[52] intercept   : AIC=1666.654, Time=3.13 sec
ARIMA(0,1,1)(0,0,1)[52] intercept   : AIC=inf, Time=3.19 sec
ARIMA(0,1,0)(0,0,0)[52]             : AIC=1699.752, Time=0.02 sec
ARIMA(1,1,0)(0,0,0)[52] intercept   : AIC=1665.705, Time=0.12 sec
ARIMA(1,1,0)(0,0,1)[52] intercept   : AIC=1666.647, Time=2.60 sec
ARIMA(1,1,0)(1,0,1)[52] intercept   : AIC=1668.647, Time=5.35 sec
ARIMA(2,1,0)(0,0,0)[52] intercept   : AIC=1647.638, Time=0.07 sec
ARIMA(2,1,0)(1,0,0)[52] intercept   : AIC=1647.968, Time=5.39 sec
ARIMA(2,1,0)(0,0,1)[52] intercept   : AIC=1647.993, Time=3.75 sec
ARIMA(2,1,0)(1,0,1)[52] intercept   : AIC=1649.968, Time=8.39 sec
ARIMA(3,1,0)(0,0,0)[52] intercept   : AIC=1634.944, Time=0.10 sec
ARIMA(3,1,0)(1,0,0)[52] intercept   : AIC=1636.693, Time=8.38 sec
ARIMA(3,1,0)(0,0,1)[52] intercept   : AIC=1636.708, Time=5.15 sec
ARIMA(3,1,0)(1,0,1)[52] intercept   : AIC=inf, Time=14.20 sec
ARIMA(4,1,0)(0,0,0)[52] intercept   : AIC=1633.910, Time=0.14 sec
ARIMA(4,1,0)(1,0,0)[52] intercept   : AIC=1635.745, Time=2.38 sec
ARIMA(4,1,0)(0,0,1)[52] intercept   : AIC=1635.761, Time=6.20 sec
ARIMA(4,1,0)(1,0,1)[52] intercept   : AIC=inf, Time=16.45 sec
ARIMA(5,1,0)(0,0,0)[52] intercept   : AIC=1630.284, Time=0.41 sec
ARIMA(5,1,0)(1,0,0)[52] intercept   : AIC=1631.765, Time=6.28 sec
ARIMA(5,1,0)(0,0,1)[52] intercept   : AIC=1631.805, Time=5.67 sec
ARIMA(5,1,0)(1,0,1)[52] intercept   : AIC=inf, Time=15.37 sec
ARIMA(6,1,0)(0,0,0)[52] intercept   : AIC=1630.874, Time=0.45 sec
ARIMA(5,1,1)(0,0,0)[52] intercept   : AIC=inf, Time=0.66 sec
ARIMA(4,1,1)(0,0,0)[52] intercept   : AIC=inf, Time=0.56 sec
ARIMA(6,1,1)(0,0,0)[52] intercept   : AIC=inf, Time=0.80 sec
ARIMA(5,1,0)(0,0,0)[52]             : AIC=1628.369, Time=0.20 sec
ARIMA(5,1,0)(1,0,0)[52]             : AIC=1629.844, Time=3.39 sec
ARIMA(5,1,0)(0,0,1)[52]             : AIC=1629.883, Time=3.79 sec
ARIMA(5,1,0)(1,0,1)[52]             : AIC=inf, Time=5.90 sec
ARIMA(4,1,0)(0,0,0)[52]             : AIC=1631.963, Time=0.08 sec
ARIMA(6,1,0)(0,0,0)[52]             : AIC=1628.991, Time=0.26 sec
ARIMA(5,1,1)(0,0,0)[52]             : AIC=1614.244, Time=0.47 sec
ARIMA(5,1,1)(1,0,0)[52]             : AIC=1614.307, Time=6.95 sec
ARIMA(5,1,1)(0,0,1)[52]             : AIC=1614.428, Time=4.40 sec
ARIMA(5,1,1)(1,0,1)[52]             : AIC=inf, Time=7.27 sec
ARIMA(4,1,1)(0,0,0)[52]             : AIC=1613.564, Time=0.23 sec
ARIMA(4,1,1)(1,0,0)[52]             : AIC=1614.206, Time=3.28 sec
ARIMA(4,1,1)(0,0,1)[52]             : AIC=1614.355, Time=3.48 sec
ARIMA(4,1,1)(1,0,1)[52]             : AIC=inf, Time=8.28 sec
ARIMA(3,1,1)(0,0,0)[52]             : AIC=1611.646, Time=0.29 sec
ARIMA(3,1,1)(1,0,0)[52]             : AIC=1612.206, Time=3.24 sec
ARIMA(3,1,1)(0,0,1)[52]             : AIC=1612.356, Time=2.45 sec
ARIMA(3,1,1)(1,0,1)[52]             : AIC=inf, Time=5.55 sec
ARIMA(2,1,1)(0,0,0)[52]             : AIC=1610.019, Time=0.12 sec
ARIMA(2,1,1)(1,0,0)[52]             : AIC=1610.438, Time=3.43 sec
ARIMA(2,1,1)(0,0,1)[52]             : AIC=1610.594, Time=2.02 sec
ARIMA(2,1,1)(1,0,1)[52]             : AIC=inf, Time=4.26 sec
ARIMA(1,1,1)(0,0,0)[52]             : AIC=1609.541, Time=0.07 sec
ARIMA(1,1,1)(1,0,0)[52]             : AIC=1610.207, Time=1.71 sec
ARIMA(1,1,1)(0,0,1)[52]             : AIC=1610.309, Time=1.88 sec
ARIMA(1,1,1)(1,0,1)[52]             : AIC=1612.024, Time=7.56 sec
ARIMA(0,1,1)(0,0,0)[52]             : AIC=1608.209, Time=0.05 sec
ARIMA(0,1,1)(1,0,0)[52]             : AIC=1608.533, Time=0.97 sec
ARIMA(0,1,1)(0,0,1)[52]             : AIC=1608.656, Time=1.01 sec
ARIMA(0,1,1)(1,0,1)[52]             : AIC=1610.357, Time=2.37 sec
ARIMA(0,1,2)(0,0,0)[52]             : AIC=1609.353, Time=0.11 sec
ARIMA(1,1,0)(0,0,0)[52]             : AIC=1663.708, Time=0.02 sec
ARIMA(1,1,2)(0,0,0)[52]             : AIC=1611.960, Time=0.17 sec
ARIMA(0,1,1)(0,0,0)[52] intercept   : AIC=inf, Time=0.12 sec

Best model:  ARIMA(0,1,1)(0,0,0)[52]          
Total fit time: 203.303 seconds