I am new to R and new to time series modeling.
I have a set of variables (var1, var2, var3, var4, var5) for which I have
historical yearly data.
I am trying to use this data to produce a prediction of var1, 3 years into
the future.
I have a few basic questions:
1) I am able to read in my data, and convert it to a time series format
using 'ts.'
data_ts <- ts(data, start = 1988, end = 2005, frequency = 1, deltat = 1)
However, I am not able to refer to the individual columns or variables of my
new time series object. For example, I am able to reference 'var1' by
typing, data$var1, but I can not do the same by using data_ts$var1. I don't
see how I can use data_ts without being able to reference the individual
columns in my dataset.
2) Since I'm trying to build a multivariate time series model, I want to
find the correlations of var1 with my other variables (var1, var2, ...etc.)
and their lagged values.
But since I'm trying to produce a forecast for 3 years into the future, I
want to find the ccf between var1 and my other variables lagged 3 years. I
tried doing:
ccf(var1, lag(var2, 3))
but I get the following error:
Error in na.fail.default(ts.union(as.ts(x), as.ts(y))) :
missing values in object
Does anyone know how to use the lag funciton and ccf together?
3) Suppose var1 and var2 are both of length 20.
I would expect the correlation of the fourth lag of ccf(var1, var2) to be
the same as lag zero of:
ccf(var1[1:17], var2[4:20]), but they are not. Can someone explain why not?
4) How do I interpret the negative lags produced from the ccf function?
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