I'm using S-Plus 7.0.3 under XP on a dual-Opteron box with 4 GB of RAM. I'm trying to do a two-sample permutation test using large objects. Specifically, I have two vectors: one has a length of 23152
I can't quite figure out what the cor() function does with the different na.methods "omit" and "available". I find that each of these methods yields a different answer, even if there is no missing da
This is wild... I did this with S-Plus 7.0.0 for windows under XP. I'm now at home, with S-Plus 6.2 under Windows XP and get exactly the same results I got on my work machine: cor() using na.method =
I have a data frame (several, really) that have a structure I'm trying to unravel. After column 1, which contains duplicates, each succeeding column contains new data *plus* all the data form column
I apologize for not being more clear; I admit being in a hurry to get the kids from day care. Regardless, I don't mean for the group to divine my problem based on my poor description: yes, these data
The functions provided by Sam Buttrey and Tom Jagger both do exactly what I need to do, and both use parts of S about which I was ignorant. I am now slightly less ignorant and thank both of you for r
I'll review my problem using a simple example. Consider two vectors, x and y. The vector y contains all of x, plus additional data. One twist is that both contain duplicate values, while the other tw
I have a very simply problem that, while I can think of a way to do it, I can't think of an elegant way. Here's a simplified version: I have two vectors or different lengths, m and n. I wish to gener
This works. Also, while I have the beta release of the latest resample library, I was utterly ignorant of the bootstrap2 function. Thanks for the enlightenment! Kim Elmore new.xy <- c(x,y) which.xy
This is not strictly an S-Plus question. I'm trying to understand discrepancies I see between results form a KS GOF test and a Chi-Square GOF test. I have a Talagrand diagram (also known as a rank hi
There is clearly something I don't understand about how these work, so, benighted as I am, I appeal to the group for assistance. Start with chisq.gof. I want to test GOF against a uniform distributio
Thanks to all for your replies. I just escaped (I mean it that way, too) a meeting and, while there, I pondered this some more and it hit me, (insert a Homer Simpson "Doh!" here), that rounding may w
Now that I understand my error when looking at chi-square GOF results using my dummy data, I tried the same thing with a KS GOF test. My benighted state continues. Here is what I see: [1] 0.5324786 [
Now, this is an interesting approach, one I've not seen discussed anywhere. I find Monte Carlo techniques appealing; how would I go about doing this? Cheers, Kim Elmore The KS test is not intended fo
Hi Nels, Thanks for the reply. This is intrigueing, but I'm wondering: if the continuous KS test can't "properly" be applied to discrete data, then what you propose sounds something like: "improperly