R - ave rollapply error: k <= n is not TRUE

Question

I am trying to calculate a rolling mean of value grouped by multiple dimensions in R. Something I would do in SQL in the following way:

AVG(value) OVER 
   (PARTITION BY dim1, dim2 ORDER BY date 
       RANGE BETWEEN 5 PRECEDING AND CURRENT ROW)

The following seems to work if I select just a few dimensions:

s <- ave(df$value, 
     list(df$dim1, df$dim2), 
     FUN= function(x) rollapply(x, 5, mean, align='right'))

but gives the following error when I select full set of dimensions:

Error: k <= n is not TRUE 

I get the same error when I run:

rollapply(c(1:2), 3, mean, align='right')

so I guess the issue is that some combinations of dimensions do not have enough values to calculate mean.

How could I overcome it? I am fine with having a NA as a result for those combinations. Any help would be much appreciated..

Leuctra

Well, in your last example, you are trying to use the last three values on each iteration...but the iteration vector c(1:2) only has two! – Dextrad

Yes, I am aware what the issue is, second example is just to illustrate it. The question is, how can I overcome it and get NA if there are to few elements to calculate rollapply instead of getting an error message. – Leuctra

Answer 1

roll_meanr from the RcppRoll package will do this by default:

library(RcppRoll)
> roll_meanr(c(1:2), 3)
# [1] NA NA

Glance

Answer 2

rollapply(c(1:10), 3, mean, align='right', fill=NA) should do the trick, provided your vector is long enough to produce any data.

note that rollapply(c(1:2), 3, mean, align='right', fill=NA) still returns the error for the reason stated by @robert-krzyzanowski

Auer