[数据以季度为单位，从1955年到2019年，我正在尝试通过将采样周期递增一个点，然后对该新采样周期重复估算和预测过程来获得固定水平的预测，并提取未来一年（h = 4）的预测。我想从2017年第二季度开始进行预测。
但是我尝试过使用for循环，但是它根本不起作用，是否有可能将此代码压缩为for循环函数
a <- ts(data$UK.GDP.UA.MP, start = c(1955,1), end = c(2016,4), frequency = 4)
aa <- auto.arima(a)
aa
forecast(aa,h = 4)
b <- ts(data$UK.GDP.UA.MP, start = c(1955,1), end = c(2017,1), frequency = 4)
bb <- auto.arima(a)
bb
forecast(bb,h = 4)
c <- ts(data$UK.GDP.UA.MP, start = c(1955,1), end = c(2017,2), frequency = 4)
cc <- auto.arima(a)
cc
forecast(cc,h = 4)
d<- ts(data$UK.GDP.UA.MP, start = c(1955,1), end = c(2017,3), frequency = 4)
dd <- auto.arima(d)
dd
forecast(dd,h = 4)
e <- ts(data$UK.GDP.UA.MP, start = c(1955,1), end = c(2017,4), frequency = 4)
ee <- auto.arima(e)
ee
forecast(ee,h = 4)
f <- ts(data$UK.GDP.UA.MP, start = c(1955,1), end = c(2018,1), frequency = 4)
ff <- auto.arima(f)
ff
forecast(ff,h = 4)
g <- ts(data$UK.GDP.UA.MP, start = c(1955,1), end = c(2018,2), frequency = 4)
gg <- auto.arima(g)
gg
forecast(gg,h = 4)
h <- ts(data$UK.GDP.UA.MP, start = c(1955,1), end = c(2018,3), frequency = 4)
hh <- auto.arima(h)
hh
forecast(hh,h = 4)
由reprex package（v0.3.0）在2019-12-06创建