model_i= pf.ARIMAX(data=traindata,formula="EXP~CUR+CRR+D+Trade+Invest+Rate+Gov+Pro",ar=resultdf.arp[ii],ma=resultdf.mrq[ii],integ=0)try: modeli_fit= model_i.fit("MLE") bic=modeli_fit.bic EXP_pre= model.predict(h=testdata.shape[0],oos_data=testdata) mae=mean_absolute_error...
()) ## 迭代循环建立多个模型 for ii in resultdf.index: model_i = pf.ARIMAX(data=traidata,formula="C02~GasRate",ar=resultdf.arp[ii],ma=resultdf.mrq[ii],integ=0) try: modeli_fit = model_i.fit("MLE") bic = modeli_fit.bic C02_pre = model.predict(h=testdata.shape[0],oos_...
ARIMA是可以拟合时间序列数据的模型，根据自身的过去值(即自身的滞后和滞后的预测误差)“解释” 给定的时...
#建立ARIMAX模型(利用差分后的数据进行建模,实际上仍然相当于arimax(p,d,q))model=pf.ARIMAX(data=traindata,formula="EXP~CUR+CRR+D+Trade+Invest+Rate+Gov+Pro",ar=1,integ=0,ma=1) result=model.fit("MLE")print(result.summary()) 4.9模型结果拟合 #模型结果拟合model.plot_fit(figsize=(5,3)) 4....
Malaysia's petroleum fuel pricing policy has shuffled between Automatic Adjusted Formula (APM) and Managed Float System (MFS). One major problem in forecasting fuel prices is the use of the structural model. The model uses an input or independent variable, the refined fuel price also known as ...
The Wavelet-ARIMAX method, which uses wavelet analysis within the ARIMAX structure, is better at forecasting performance and model fit than the standard ARIMAX model. Based on climatic variables, Wavelet-ARIMAX can accurately predict diarrheal occurrence, as indicated by the mean absolute error (MAE)...