[R] Efficient way to Calculate the squared distances for a set of vectors to a fixed vector

[Daniel Malter]

Let's say your fixed vector is x, and y is the list of vectors that you want
to create the squared distance to x with, then:

x<-c(1:5)
y<-list()
y[[1]]<-sample(c(1:5),5)
y[[2]]<-sample(c(1:5),5)
y[[3]]<-sample(c(1:5),5)
y

distances<-lapply(y,function(a,b) crossprod(a-b), b=x) 

#lapply goes over the list elements of y and executes the function for each
of these list elements
#the current list element of "y" is plugged in for "a" and "x" is plugged in
for "b" and the crossproduct is formed

distances<-unlist(distances)

HTH,
Daniel





Wei Wu wrote:
> 
> I am pretty new to R. So this may be an easy question for most of you.
>  
> I would like to calculate the squared distances of a large set (let's say
> 20000) of vectors (let's say dimension of 5) to a fixed vector.
>  
> Say I have a data frame MY_VECTORS with 20000 rows and 5 columns, and one
> 5x1 vector y. I would like to efficiently calculate the squared
> distances between each of the 20000 vectors in MY_VECTORS and y.
>  
> The squared distance between two vectors x and y can be calculated:
> distance <- crossprod(x-y)
>  
> Without looping, what is the efficient code to achieve this?
>  
> Thanks.
> 
> ______________________________________________
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