[R] Random sampling while keeping distribution of nearest neighbor distances constant.
Nordlund, Dan (DSHS/RDA)
NordlDJ at dshs.wa.gov
Thu Aug 13 01:00:50 CEST 2009
> -----Original Message-----
> From: r-help-bounces at r-project.org [mailto:r-help-bounces at r-project.org] On
> Behalf Of Emmanuel Levy
> Sent: Wednesday, August 12, 2009 3:05 PM
> To: r-help at stat.math.ethz.ch
> Cc: dev djomson
> Subject: [R] Random sampling while keeping distribution of nearest neighbor
> distances constant.
>
> Dear All,
>
> I cannot find a solution to the following problem although I imagine
> that it is a classic, hence my email.
>
> I have a vector V of X values comprised between 1 and N.
>
> I would like to get random samples of X values also comprised between
> 1 and N, but the important point is:
> * I would like to keep the same distribution of distances between the X values *
>
> For example let's say N=10 and I have V = c(3,4,5,6)
> then the random values could be 1,2,3,4 or 2,3,4,5 or 3,4,5,6, or 4,5,6,7 etc..
> so that the distribution of distances (3 <-> 4, 3 <->5, 3 <-> 6, 4 <->
> 5, 4 <-> 6 etc ...) is kept constant.
>
> I couldn't find a package that help me with this, but it looks like it
> should be a classic problem so there should be something!
>
> Many thanks in advance for any help or hint you could provide,
>
> All the best,
>
> Emmanuel
>
Emmanuel,
I don't know if this is a classic problem or not. But given your description, you write your own function something like this
sample.dist <- function(vec, Min=1, Max=10){
diffs <- c(0,diff(vec))
sum_d <- sum(diffs)
sample(Min:(Max-sum_d),1)+cumsum(diffs)
}
Where Min and Max are the minimum and maximum values that you are sampling from (Min=1 and Max=10 in your example), and vec is passed the vector that you are sampling distances from. This assumes that your vector is sorted smallest to largest as in your example. The function could be changed to accommodate a vector that isn't sorted.
> V <- sort(sample(1:100,4))
> V
#[1] 46 78 82 95
> sample.dist(V, Min=1, Max=100)
#[1] 36 68 72 85
> sample.dist(V, Min=1, Max=100)
#[1] 12 44 48 61
>
This should get you started at least. Hope this is helpful,
Dan
Daniel J. Nordlund
Washington State Department of Social and Health Services
Planning, Performance, and Accountability
Research and Data Analysis Division
Olympia, WA 98504-5204
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