In preparation for developing the Bonferroni calculation and fitting software, I thought I’d just write a quick OWA calculator. Although the concept of the OWA calculation is quite simple, it is one of the most powerful and widely used aggregation functions. It was formally defined by Yager in 1988.

The key implementation is the sorting of the *x* values, other than this, it can be calculated in the same manner as the WAM. For high dimensional data, the sort algorithm can be quite an impediment to efficient application. My colleague, Gleb Beliakov has tackled this problem here and, of course, also has already developed tools for OWA calculation and fitting in other languages.

**Standard Function Specification**

required input: x-vector, weights (optional), n

OWA <- function(x,w=array(1/n,n) {
sum(sort(x,decreasing= TRUE)*(w))
}

**Calculation of an input data set**

required input: x-values, w (optional)

# Define the function
OWA <- function(x,w=array(1/n,n) {
sum(sort(x,decreasing= TRUE)*(w))
}
# read weights and data
w <- array(0,n)
x.data <-read.table("documents/R/inputs6.txt",header=TRUE)
y.values <- array(0,nrow(x))
# sort data
for(i in 1:nrow(x)) {
x.data[i,]<-sort(x.data[i,],decreasing = TRUE)
}
# calc values
for(i in 1:nrow(x.data)) {
y[i] <- OWA(x.data[i,],w)
}
# merge into single file if you like and export to file
write.table(cbind(x.data,y),"documents/R/OWAout1.txt")

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