search for: qeii

...= T, cex.title = 1.2, title = "Expected Tau", text = c("30 ms", "80 ms", "130 ms", "180 ms", "230 ms"), space = "right", ) ) -- Mike Lawrence, BA(Hons) Research Assistant to Dr. Gail Eskes Dalhousie University & QEII Health Sciences Centre (Psychiatry) Mike.Lawrence at Dal.Ca "The road to Wisdom? Well, it's plain and simple to express: Err and err and err again, but less and less and less." - Piet Hein

Dear R, I'm looking for exact p-values for Spearman's rank correlation in the presence of ties. This is available in StatXact and SPSS, but I haven't yet found it in R. Has anyone implemented this? -- Paul H Artes Assist Prof, Ophth Vis Sci Dalhousie University, QEII Eye Care Centre Halifax, NS, CANADA

...the test? Does it sound appropriate for my purposes (if not, how about the other tests suggested above)? How does it differ from the Lack-of-Fit test? Any help would be greatly appreciated. Cheers, Mike -- Mike Lawrence, BA(Hons) Research Assistant to Dr. Gail Eskes Dalhousie University & QEII Health Sciences Centre (Psychiatry) Mike.Lawrence at Dal.Ca "The road to Wisdom? Well, it's plain and simple to express: Err and err and err again, but less and less and less." - Piet Hein

...need conformation that cross-validation doesn't work with custom functions, and if someone could explain to me why that is the case it would be greatly appreciated. Thanks, Sam Stewart -- Sam Stewart, MMath Research Statistician, Diagnostic Imaging Rm 3016, 3 South Victoria Building VG Site, QEII Health Sciences Centre 1278 Tower Rd, Halifax, NS, B3H 2Y9 [[alternative HTML version deleted]]

Dear R-Mastermind Within a while or a for-loop, is there a way that I can save to disk the results of the previous calculations at the end of each loop with filenames called "file01.Rdata", "file02.Rdata" etc? So far, I have tried to write the outcome of each loop in a 3 dimensional array and saved it just once after the loop. Or is there another way so that I can keep

Hi, Thanks for reading. I am running a process in R for microarray data analysis. RedHat Enterprise Linux 4, dual AMD CPU, 6G memory. However, the R process use only a total of <200M memory. And the CPU usage is total to ~110% for two. The program takes at least 2 weeks to run at the current speed. Is there some way we can increase the usage of CPUs and memories and speed up? Any