[R] Sampling a matrix with different probability distributions
slomascolo at gmail.com
Tue May 5 19:37:30 CEST 2009
Greg Snow-2 wrote:
> The sample function has a prob argument that can be used to sample with
> unequal probabilities. It sounds like you can just pass in the species
> abundance vector to prob and it will do what you want.
> It might be that my question is even more basic than it sounds: I have
> tried what you say, but I may just be writing it wrong as I get an error
> message. I wrote:
> reduced.M <- matrix(table( factor( sample(rep(M.index,M),800), M.index
> but I get and error message saying that the prob argument is "unused"". I
> have also tried prob=unif, or directly prob=c(10, 9, 6, 5, 3), but I get
> the same error message. Any hints as to how I am passing the prob argument
> wrong? This is probably too basic...
> Thanks, Silvia.
> Gregory (Greg) L. Snow Ph.D.
> Statistical Data Center
> Intermountain Healthcare
> greg.snow at imail.org
>> -----Original Message-----
>> From: r-help-bounces at r-project.org [mailto:r-help-bounces at r-
>> project.org] On Behalf Of Silvia Lomascolo
>> Sent: Tuesday, May 05, 2009 9:52 AM
>> To: r-help at r-project.org
>> Subject: [R] Sampling a matrix with different probability distributions
>> I need to sample a matrix according to different distributions, instead
>> just randomly. Here is some code that will hopefully clarify what I
>> I have a matrix M of 1287 interactions between species in rows and
>> in columns, according to their abundance:
>> pla<- c(10, 9, 6, 5, 3) #abundance of pla species
>> pol<- c(14, 10, 9, 4, 2) #abundance of pol species
>> M<-pla%*%t(pol) #matrix of 1287 interactions according to pla and pol
>> [,1] [,2] [,3] [,4] [,5]
>> [1,] 140 100 90 40 20
>> [2,] 126 90 81 36 18
>> [3,] 84 60 54 24 12
>> [4,] 70 50 45 20 10
>> [5,] 42 30 27 12 6
>> Thanks to help from people in this forum, I was able to randomly sample
>> interactions from matrix M and obtain a subset of the interactions in a
>> smaller matrix called reduced.M:
>> M.index <- 1:length(M)
>> reduced.M <- matrix(table( factor( sample(rep(M.index,M),800),
>> [,1] [,2] [,3] [,4] [,5]
>> [1,] 77 62 56 25 15
>> [2,] 83 53 51 21 11
>> [3,] 57 34 28 18 10
>> [4,] 51 31 21 14 4
>> [5,] 27 21 19 6 5
>> Now I need to sample again, not randomly, but according to different
>> distributions. For example, I need to sample according to the
>> abundance of
>> species pla, (pla vector written above). The result should be that I
>> my first row more intensely than my second row, and the last row should
>> the least intensely sampled, in proportion to my row species abundance.
>> the same token, I want to sample with a uniform distribution as well.
>> do I do this?
>> Thanks, as usual! Silvia.
>> View this message in context: http://www.nabble.com/Sampling-a-matrix-
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>> PLEASE do read the posting guide http://www.R-project.org/posting-
>> and provide commented, minimal, self-contained, reproducible code.
> R-help at r-project.org mailing list
> PLEASE do read the posting guide
> and provide commented, minimal, self-contained, reproducible code.
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