Looping through time-series data in R - r

Question

I am trying to:
1) fit arma model on given data
2) obtain forecast for the next day
3) add forecast to the data
4) return to 1)
Code I have written:
library(forecast)
dates<- seq(as.Date(today), by="days", length=10)
sim<- rnorm(10)
tsdata<- as.ts(cbind(as.xts(dates),sim))
temp<- tsdata
for(i in 1:10){
Arma1[i]<- Arima(temp, order=c(2,0,2))
fcasts1[[i]]<- forecast(Arma1[i], h=1)
fore1[i]<-unlist(fcasts1[[i]]$mean[1])
temp<- as.ts(rbind(as.xts(temp),fore1[i]))
}
This gives me an error:
Error in x - fits : non-numeric argument to binary operator
In addition: Warning messages:
1: In Arma1[i] <- Arima(temp, order = c(2, 0, 2)) :
number of items to replace is not a multiple of replacement length
2: In mean.default(x, na.rm = TRUE) :
argument is not numeric or logical: returning NA
How can I fix this?

Answer 1

I am not exactly sure what you want to do and if the timeindex for the forecast-values is correct this way, but the loop in this code should at least work:
library(xts)
library(forecast)
dates <- seq(Sys.Date(), by="days", length=10)
sim <- rnorm(10)
tsdata <- xts(sim, order.by = dates)
temp.old <- tsdata
temp <- tsdata
Arma1 <- list(10)
fcasts1 <- list(10)
fore1 <- list(10)
temp <- list(10)
for(i in 1:10){
Arma1[[i]] <- Arima(temp.old, order=c(2,0,2))
fcasts1[[i]] <- forecast(Arma1[[i]], h=1)
fore1[i] <- unlist(fcasts1[[i]]$mean)
temp[i] <- as.xts(fore1[[i]], order.by = dates[i])
}