Rank-based p-value on large dataset
The x's and y's are different sets--210,000 values altogether. That is really the issue--they can't just be sorted, at least that I can see.... Sean
On Mar 3, 2005, at 5:38 PM, Huntsinger, Reid wrote:
When you say the 130,000 points are from the empirical distribution, how did you get them? Is each one really one of the values of y? If you sorted y first, would you know which one (ie which index) each x is? (Sorting 80,000 elements took essentially no time at all on my sub-gigahertz Pentium III.) But maybe that's not an option... more details would help. Reid Huntsinger -----Original Message----- From: r-help-bounces at stat.math.ethz.ch [mailto:r-help-bounces at stat.math.ethz.ch] On Behalf Of Sean Davis Sent: Thursday, March 03, 2005 5:22 PM To: r-help Subject: [R] Rank-based p-value on large dataset I have a fairly simple problem--I have about 80,000 values (call them y) that I am using as an empirical distribution and I want to find the p-value (never mind the multiple testing issues here, for the time being) of 130,000 points (call them x) from the empirical distribution. I typically do that (for one-sided test) something like loop over i in x p.val[i] = sum(y>x[i])/length(y) and repeat for all i. However, length(x) is large here as is length(y), so this process takes quite a long time. Any suggestions? Thanks, Sean
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