There is also rollmean in the zoo package which might be slightly
faster since its optimized for that operation.
k * rollmean(x, k)
e.g.
> 2 * rollmean(1:4, 2)
[1] 3 5 7
will give a rolling sum. runmean in the caTools package is even faster.
On Fri, Apr 2, 2010 at 2:31 PM, Jorge Ivan Velez
<jorgeivanve...@gmail.com> wrote:
> Hi Andy,
>
> Take a look at the rollapply function in the zoo package.
>
>> require(zoo)
> Loading required package: zoo
>> x <- 1:4
>> rollapply(zoo(x), 1, sum)
> 1 2 3 4
> 1 2 3 4
>> rollapply(zoo(x), 2, sum)
> 1 2 3
> 3 5 7
>> rollapply(zoo(x), 3, sum)
> 2 3
> 6 9
>> rollapply(zoo(x), 4, sum)
> 2
> 10
>
> # all at once
> sapply(1:4, function(r) rollapply(zoo(x), r, sum))
>
>
> HTH,
> Jorge
>
>
> On Fri, Apr 2, 2010 at 2:24 PM, Andy Rominger <> wrote:
>
>> Hello,
>>
>> I'd like to take all possible sub-summands of a vector in the quickest and
>> most efficient way possible. By "sub-summands" I mean for each sub-vector,
>> take its sum. Which is to say: if I had the vector
>>
>> x<-1:4
>>
>> I'd want the "sum" of x[1], x[2], etc. And then the sum of x[1:2], x[2:3],
>> etc. And then...so on.
>>
>> The result would be:
>> 1 2 3 4
>> 2 5 7
>> 6 9
>> 10
>>
>> I can do this with for loops (code below) but for long vectors (10^6
>> elements) looping takes more time than I'd like. Any suggestions?
>>
>> Thanks very much in advance--
>> Andy
>>
>>
>> # calculate sums of all sub-vectors...
>> x <- 1:4
>>
>> sub.vect <- vector("list",4)
>>
>> for(t in 1:4) {
>> maxi <- 4 - t + 1
>> this.sub <- numeric(maxi)
>> for(i in 1:maxi) {
>> this.sub[i] <- sum(x[i:(i+t-1)])
>> }
>> sub.vect[[t]] <- this.sub
>> }
>>
>> sub.vect
>>
>> [[alternative HTML version deleted]]
>>
>> ______________________________________________
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>> https://stat.ethz.ch/mailman/listinfo/r-help
>> PLEASE do read the posting guide
>> http://www.R-project.org/posting-guide.html
>> and provide commented, minimal, self-contained, reproducible code.
>>
>
> [[alternative HTML version deleted]]
>
> ______________________________________________
> R-help@r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>
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