我希望使用statsmodels从训练模型中获取参数,并将这些参数用于预测测试模型的值。
我的代码:
我的代码:
import pandas as pd
import numpy as np
import statsmodels.api as sm
#Generate data
index = pd.date_range('2000-1-1', periods=200, freq='M')
df = pd.DataFrame({'data':np.random.random(200)}, index=index)
df_train = df[df.index < df.index[100]]
df_test = df
#Set up model
mod_train = sm.tsa.AR(df_train)
res_train = mod_train.fit(max_lag=20,trend='nc')
params_train = res_train.params
mod_test = sm.tsa.AR(df_test)
#Use parameters to predict test data
mod_test.predict(params_train,start = df.index[100],dynamic=False)
错误信息:
---------------------------------------------------------------------------
AttributeError Traceback (most recent call last)
<ipython-input-309-a6eb40a5ff54> in <module>()
9 params_train = res_train.params
10 mod_test = sm.tsa.AR(df_test)
---> 11 mod_test.predict(params_train,start = df.index[100],dynamic=False)
C:\Anaconda\lib\site-packages\statsmodels\tsa\ar_model.pyc in predict(self, params, start, end, dynamic)
198 raise ValueError("end is before start")
199
--> 200 k_ar = self.k_ar
201 k_trend = self.k_trend
202 method = self.method
AttributeError: 'AR' object has no attribute 'k_ar'
请问有人可以提供一个解决方法吗?我也可以考虑其他模块。谢谢!
AR
的方式是从statsmodels.tsa.ar_model.AR(...)
。你试过了吗? - N1B4