Just for make the archives more complete and simplifing the life of the
following readers.
I think to have solved my problem using the caret packages.
In this package there is a function named createData Partition that after
defining a column of interest in a data.frame allows to split a dataset in
I think you're right -- prob probably isn't quite what you need (at
least, directly): constrained sampling like this is a little trickier
-- I'll leave this to someone who knows more than me.
Michael
On Thu, Jun 14, 2012 at 9:07 AM, Guido Leoni wrote:
> Sorry I'm not sure that prob is suitable f
Sorry I'm not sure that prob is suitable for my purposes(but i'm quite
newbie with R).
If I correctly understand prob allows to set a weight for each row in the
original dataset in order to include the rows on the basis of their
weights). ... I'm not sure to correctly understanding ;-)
In my case a
sample() takes a prob = argument which lets you supply weights, which
need not sum to one so, if I understand you, you could just pass TRUEs
and FALSEs for those rows you want. If I'm wrong about that last bit,
I'm still pretty confident sample(prob = ) is the way to go.
Best,
Michael
On Thu, Jun
Dear list I wish to extract from a population genotypized for 10 SNP a
subsample of the same population of size n with similar allele frequencies.
Essentially i have a matrix of 200 rows (df) like this
Name,Condition,rs1385699_X,rs6625163_X,rs962458_X,Rs4658627_1,
sample01,Case,1,1,1,-1
sample02,Co
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