You could use filter(..., filter=rep(1,5)) to get running sums of length 5
to get your answer.  The following calls filter once to get the sum of
the negative values in each window and once to get the number of negative
values in each window, then divides to get the means.

f <- function(x, n=5) {
    sumNeg <- filter(pmin(x, 0), filter=rep(1,n)) # running sums of negative 
values
    numNeg <- filter( x < 0, filter=rep(1,n))  # running numbers of negative 
values
    as.vector(sumNeg/numNeg) # running means of negative values
}

E.g.,
> s <- c(0, 2, -3, -2, 1, -2)
> cbind(s, meanNeg = f(s, n=5))
      s   meanNeg
[1,]  0        NA
[2,]  2        NA
[3,] -3 -2.500000
[4,] -2 -2.333333
[5,]  1        NA
[6,] -2        NA

It is quick for long vectors
> ss <- floor(sin(1:1e6)*5) # one million numbers
> system.time(f(ss, 5))
   user  system elapsed
  1.036   0.040   1.079

If you want results at the ends, append (n-1)/2 0's to each end of the series
and remove the NA's that appear at those positions in the output.

The 'as.vector' is there because filter always returns a 'ts' (a class of time 
series
objects), even if the input is a simple vector.

Bill Dunlap
Spotfire, TIBCO Software
wdunlap tibco.com


> -----Original Message-----
> From: r-help-boun...@r-project.org [mailto:r-help-boun...@r-project.org] On 
> Behalf
> Of Eko andryanto Prakasa
> Sent: Wednesday, September 26, 2012 8:39 AM
> To: r-help@R-project.org
> Subject: [R] averageif and looping
> 
>  haiii
> 
> i want to know, is there any script in R to measure looping averageif (like 
> in the excel)
> .......
> for example:
> i have a vector
> row    value
> 1        0
> 2        2
> 3        -3
> 4        -2
> 5        1
> 6        -2
> 
> i want to measure the average of the vector for negative value with window 
> estimation 5
> so first mean is (-3+-2)/2
>      second mean is (-3+-2+-2)/3
> 
> ______________________________________________
> R-help@r-project.org mailing list
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> 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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