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1、m1=arima(da1,order=c(1,1,0),seasonal=list(order=c(2,1,0),period=12),method=ML)m2=arima(da1,order=c(1,1,1)m3=arima(da1,order=c(2,1,0)m4=arima(da1,order=c(0,1,3)m5 Box.test(resm2,lag=5,type=Ljung) Box-Ljung testdata: resm2 X-squared = 3.1873, df = 5, p-value = 0.6711 Box.test(resm3,lag=5,type=Ljung) B
2、ox-Ljung testdata: resm3 X-squared = 5.3676, df = 5, p-value = 0.3727 Box.test(resm4,lag=5,type=Ljung) Box-Ljung testdata: resm4 X-squared = 7.6986, df = 5, p-value = 0.1736Box.test(resm5,lag=5,type=Ljung) Box-Ljung testdata: resm5 X-squared = 3.3973, df = 5, p-value = 0.639P值均大于0.05，即模型通过再进行异常值检验结果
3、如下：McLeod.Li.test(y=resm1)McLeod.Li.test(y=resm2)McLeod.Li.test(y=resm3)McLeod.Li.test(y=resm4)McLeod.Li.test(y=resm5)选择模型2来做异方差检验ARIMA(1,1,1) pacf(resm22,lag=60)Garch（0,1）模型Garchm2= garch(resm2,order=c(0,1),cond.dist=std,trace=F)summary(Garchm2)模型系数不显著，即异方差不通过m4 - garchFit(formula = arma(1,1)+garch(1,0),data=da3,cond.dist=std) # arma(1,1)+arch(1)
