I'd like to rbind the prediction output of an arima model to my original ts series object in a melt type of data format. But I get the following error message that I don't understand:
Error in `[<-.ts`(`*tmp*`, ri, value = c(12.2567768232753, -0.0141881223732589, :
only replacement of elements is allowed
Here´s some reproducible code, with some example data from yahoo finance:
# custom function to extract years from ts object
tsyears = function (ts){
years = as.data.frame(trunc(time(ts)))
return(years)
}
library(quantmod)
sp500 = new.env()
### get some fresh data directly from yahoo finance
getSymbols("^GSPC", env = sp500, src ="yahoo", from = as.Date("1960-01-01"),to =as.Date("2010-09-29") )
GSPC = sp500$GSPC
check what we got (last 6 entries)
tail(GSPC)
#calculate annual returns from all the adjusted closes
annual=annualReturn(GSPC)
model = arima(annual,c(1,1,0))
pd = predict(model,10)
q = ts(pd$pred,start=2010,end=2020)
w = as.ts(annual,start=1960,end=2009)
e=data.frame(tsyears(q),unclass(q),"prediction")
names(e) = c("years","return","series")
w = data.frame(tsyears(w),unclass(w),"historical")
names(w) = c("years","return","series")
rbind(w,e)
What I would like to have is:
year return series
2008 5 original
2009 -3 original
2010 6 prediction
2011 4 prediction
and so forth. From then on I would melt the dataset and use it with ggplot assigning different colors to the series value.
Your tsyears
function returns a data.frame that contains a ts
object:
> str(tsyears(q))
'data.frame': 11 obs. of 1 variable:
$ x: Time-Series from 2010 to 2020: 2010 2011 2012 2013 2014 ...
> str(tsyears(w))
'data.frame': 50 obs. of 1 variable:
$ x: Time-Series from 1960 to 2009: 1960 1961 1962 1963 1964 ...
I think you intended your function to return a data.frame containing a numeric vector. You don't need it to return a data.frame though; just returning a numeric vector works fine:
tsyears <- function(ts) as.numeric(trunc(time(ts)))
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