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Hi R Users, I have two vectors, x and y, of equal length representing two types of data from two studies. I would like to test if they are similar enough to use them interchangeably. No assumptions about distributions can be made (initial tests clearly show that they are not normal). Here some result: Two-sample Kolmogorov-Smirnov test data: x and y D = 0.1091, p-value < 2.2e-16 alternative

Hello, Is there a function in R with which we could find the greatest common divisor directly? Or is there a funciton, which could help us to find the remainder of a division directly? Best wishes! Thank you! Your truly, Qing -- View this message in context: http://r.789695.n4.nabble.com/greatest-common-divisor-tp2326262p2326262.html Sent from the R help mailing list archive at

Hi, How can I generate data from multivariate gamma distribution & multivariate beta distribution? I only found command for multivariate normal only. Many thanks in advance :) Regards Rofizah [[alternative HTML version deleted]]

Dear R helpers I am working on the Bi-variate Normal distribution probabilities. I need to double integrate the following function (actually simplified form of bivariate normal distribution) f(x, y) = exp [ - 0.549451 * (x^2 + y^2 - 0.6 * x * y) ] where 2.696 < x < 3.54 and -1.51 < y < 1.98 I need to solve something like INTEGRATE (2.696 to 3.54) dx INTEGRATE [(-1.51 to 1.98)]

I have been trying to get the lme4 package installed on Mac OS X... with no success. The Mac OS binary is not available on any CRAN, and I also can¹t install the package from old source. Has anyone found a solution to this problem? I am happy to use nlme for now, but I tend to prefer to do my mixed model analyses with lmer(). Thanks, Nicholas Griffin Center for Genome Sciences Washington

Hi all, Just thought I'd post this (maybe) helpful tool I wrote. For people like me who are bad at keeping a clean environment, it's a time-saver. #simple command to get only one type of object in current environment lstype<-function(type='closure'){ inlist<-ls(.GlobalEnv) if (type=='function') type <-'closure'

Hi! I'm trying to implement in R in an easy way the negative reflection method described in Silverman (1986) on p.31, ie I have a non-negative dataset and would like to estimate the density by applying a reflection method where the reflected points have weight -1. I thought there should be a way to evaluate the wanted kernel at the required points, in other words to calculate formula (2.16):

Can someone in R Core please take a look at the attached patches to RSiteSearch() and its help page? I guess Jon is planning some changes on his site. Jon: could you elaborate on what the patch does? Best, Andy Notice: This e-mail message, together with any attachments, contains information of Merck & Co., Inc. (One Merck Drive, Whitehouse Station, New Jersey, USA 08889), and/or its