
predict之后得到的有$se 也有$pred, 在我看来 貌似楼主把$se勿当成$pred, 实际上两种方法结果是一模一样的,见下例:
rm(list=ls())
data=c(
3.833736658,
4.663384414,
4.079585869,
1.459875074,
7.380995937,
12.4913677,
2.311010476,
-1.152176691,
-22.20108727,
-12.8632299)
k=arima(data,order=c(1,0,0))
kt1=predict(k,n.ahead=10)
kt1_pred=kt1$pred
library(forecast)
kt2=forecast(k,20, level=c(80,95))
plot(forecast(k))
kt2_pred=kt2$mean
kt1_pred-kt2_pred#两者相同,故差为0