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Retrieve hypergeometric results in large scale

William Dunlap 
order() is usually a lot more useful than sort(), since, as you noticed,
sort() drops information about where each element in its output came
from.

Your example was incomplete so I made up one which I
think is similar.
  > n <- 10 ; p <- 0.7 ; k <- 0:n ; d <- dbinom(k, n, p)
  > plot(k, d) # density of binomial over its domain
If you want the indices of the largest density values whose
cumulative sum is less than 0.95 you
  > ord <- order(d, decreasing=TRUE) # indices such that d[ord] is in decreasing order
  > big <- ord[cumsum(d[ord]) < 0.95]
  > data.frame(big, d=d[big], cumsum=cumsum(d[big]))
    big         d    cumsum
  1   8 0.2668279 0.2668279
  2   9 0.2334744 0.5003024
  3   7 0.2001209 0.7004233
  4  10 0.1210608 0.8214841
  5   6 0.1029193 0.9244035
 > points(cex=2, k[big], d[big])

If you want to include the index of the density value that puts
you just over 0.95 first find the complement of the desired indices
and use setdiff to compute its complement.  E.g.,
  > ord <- order(d)
  > little <- ord[cumsum(d[ord]) < 0.05]
  > big <- setdiff(seq_along(d), little) # difference of two sets of numbers
  > big
  [1]  5  6  7  8  9 10

Bill Dunlap
Spotfire, TIBCO Software
wdunlap tibco.com

Thread (9 messages)

jas4710 Retrieve hypergeometric results in large scale Oct 1 Jeff Newmiller Retrieve hypergeometric results in large scale Oct 1 Bert Gunter Retrieve hypergeometric results in large scale Oct 1 jas4710 Retrieve hypergeometric results in large scale Oct 1 jas4710 Retrieve hypergeometric results in large scale Oct 1 jas4710 Retrieve hypergeometric results in large scale Oct 1 Bert Gunter Retrieve hypergeometric results in large scale Oct 1 Rui Barradas Retrieve hypergeometric results in large scale Oct 1 William Dunlap Retrieve hypergeometric results in large scale Oct 1