[R] generate 3 distinct random samples without replacement

rex.dwyer at syngenta.com rex.dwyer at syngenta.com
Mon Mar 7 23:31:11 CET 2011


Cesar, I think your basic misconception is that you believe 'sample' returns a list of indices into the original vector.  It does not; it returns actual elements of the vector:

> sample(runif(100),3)
[1] 0.4492988 0.0336069 0.6948440

I'm not sure why you keep resetting the seed, but if it's important, replace
d2<-d1[-i]
with
d2<- setdiff(d1,i)

Otherwise Duncan's suggestion is must nicer:
s = sample(d1,300,replace=FALSE)
s1 = sort(s[1:100])
s2 = sort(s[101:200])
s3 = sort(s[201:300])
If what you actually need are indices into the original vector, replace d1 with length(d1).

(When you say 'distinct', I'm assuming you mean 'disjoint'.)

-----Original Message-----
From: r-help-bounces at r-project.org [mailto:r-help-bounces at r-project.org] On Behalf Of Duncan Murdoch
Sent: Monday, March 07, 2011 3:52 PM
To: Cesar Hincapié
Cc: r-help at r-project.org
Subject: Re: [R] generate 3 distinct random samples without replacement

On 07/03/2011 2:17 PM, Cesar Hincapié wrote:
> Hello:
>
> I wonder if I could get a little help with random sampling in R.
>
> I have a vector of length 7375.  I would like to draw 3 distinct random samples, each of length 100 without replacement.  I have tried the following:
>
> d1<- 1:7375
>
> set.seed(7)
> i<- sample(d1, 100, replace=F)
> s1<- sort(d1[i])
> s1
>
> d2<- d1[-i]
> set.seed(77)
> j<- sample(d2, 100, replace=F)
> s2<- sort(d2[j])
> s2
>
> d3<- d2[-j]
> set.seed(777)
> k<- sample(d3, 100, replace=F)
> s3<- sort(d3[k])
> s3
>
> D<- data.frame(a=s1,b=s2,c=s3)
>
>
> However, s2 is only 97 elements long, and s3, only 96 long.
>
> I would appreciate any suggestions on a better approach.
> I'm also curious to know why my second and third samples are less than 100 elements in length.

If you want 3 non-overlapping, non-repeating samples of 100, why not
draw one sample of 300, and take 3 subsets of it?

The reason you were finding shorter samples is because you were using j
and k as indices into vectors d2 and d3 that didn't have enough
elements, and then you sorted the result, losing the NAs.  For example,

d2 <- 1:10
d2[10:12]
sort(d2[10:12])

See ?sort for an explanation of how to keep NA values when you sort.

Duncan Murdoch

> Thanks for your time and consideration,
>
> Cesar A. Hincapié, DC, MHSc
>
> Research Fellow, Division of Health Care and Outcomes Research, Toronto Western Research Institute
> PhD Candidate in Epidemiology, Dalla Lana School of Public Health, University of Toronto
> e. cesar.hincapie at utoronto.ca
>
>
>
>
>
>       [[alternative HTML version deleted]]
>
>
>
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