similar to: Simple General Statistics and R question (with 3 line example) - get z value from pairwise.wilcox.test

Hello all, I have a SAMBA share called "share_a" and it is working fine (below is a snapshot of it): [share_a] path = /shares/share_a browseable = no valid users = @group_a @group_b @group_c write list = @group_a @group_b read list = @group_c create mode = 777 directory mode = 777 Inside this share there's a lot of sub-folders. The problem is: How can I give to one of these

Hi everybody, im new here, and I have problem. Im running samba 3beta3 at gentoo linux. Do anybody know how to resolve something like this: There are three groups in AD group_a, and group_b and group_c Members of group_a are user_0, user_1, user_2 Members of group_b are user_3, user_4, user_5 Members of group_c are user_6 and group_b If i try to do getent group At my linux box i got

So the problem is that smbd session processes will forever cache the POSIX group memberships that the logged in user possesses. Consider a following example: *smb.conf: * [share_a] path = /mnt/a valid users = dude *ls -l /mnt:* drwxrwxr-x root group_a a */etc/group:* group_a:*:2000:user Now, a client mounts *share_a* as *dude* and has R/W access to it via his *group_a* group membership. Then,

Hi, #working directory data1 #changed name data to data1.? Added some files in each of sub directories a1, a2, etc. ?indx1<- indx[indx!=""] lapply(indx1,function(x) list.files(x)) #[[1]] #[1] "a1.txt"??????? "mmmmm11kk.txt" #[[2]] #[1] "a2.txt"??????? "mmmmm11kk.txt" #[[3]] #[1] "a3.txt"??????? "mmmmm11kk.txt" #[[4]] #[1]

Hello, If I have a dataframe: example(data.frame) zz<-c("aa_bb","bb_cc","cc_dd","dd_ee","ee_ff","ff_gg","gg_hh","ii_jj","jj_kk","kk_ll") ddd <- cbind(dd, group = zz) and I want to divide the column named group by the "_", how would I do this? so instead of the first row being x

On Tue, Feb 19, 2019 at 06:13:09PM +0100, Eugene Pankov via samba wrote: > So the problem is that smbd session processes will forever cache the POSIX > group memberships that the logged in user possesses. Consider a following > example: > > *smb.conf: * > [share_a] > path = /mnt/a > valid users = dude > > *ls -l /mnt:* > drwxrwxr-x root group_a a > >

Credentials are not changed - UID/GID/SID are still the same afterwards. The user is simply being added to another group. On Fri, Feb 22, 2019 at 5:58 PM Jeremy Allison <jra at samba.org> wrote: > On Tue, Feb 19, 2019 at 06:13:09PM +0100, Eugene Pankov via samba wrote: > > So the problem is that smbd session processes will forever cache the > POSIX > > group memberships

Hello, I implemented two functions reshape_long and reshape_wide (see full working example below) to reshape data frames. I created several small examples and the two functions seemed to work properly. However, using the reshape_wide function on my real data sets (about 200.000 to 300.000 rows) failed. What happens is set all values for X, Y and Z were set to 1. The structure of my real data

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Dear R Core, pairwise.wilcox.test does not handle "paired = TRUE" correctly; e.g. set.seed(13) x <- rnorm(20) g <- c(rep(1, 10), rep(2, 10)) wilcox.test(x ~ g)$p.value # 0.075 pairwise.wilcox.test(x, g)$p.value # 0.075, o.k wilcox.test(x ~ g, paired = TRUE)$p.value # 0.105 pairwise.wilcox.test(x, g, paired = TRUE)$p.value # 0.075, wrong The line wilcox.test(xi, xj,

Hi! I have been working several years with R but it's my first public question. I hope I'll be clear :) . This question is related to obtaining letter-based representation of non-parametric pairwise comparisons. I have a dataframe with this structure (but with quite more rows and cols): A B C factor 1 2 2 one 2 1 2 one 2 2 3 two 2 3 2 two 1 4 2 three 9 8 1 three I have no normality,

does anybody know why there are the two warnings in the example above? Regards Knut > day_4 [1] 540 1 1 1 1 1 1 300 720 480 > day_1 [1] 438 343 1 475 1 562 500 435 1045 890 > is.vector (day_1) [1] TRUE > is.vector (day_4) [1] TRUE > wilcox.test(day_4 ,day_1,paired=TRUE,alternative="two.sided",exact=TRUE,conf.int=TRUE) Wilcoxon

The point estimates produced by wilcox.test are perverse (not wrong, just brain damaged). The Hodges-Lehmann estimator that goes with the signed rank test is the median of the Walsh averages. The Hodges-Lehmann estimator that goes with the rank sum test is the median of the pairwise differences. wilcox.test agrees except that it uses the following very peculiar definition of "sample

Hi all, I have being using wilcox.test to test for differences between 2 independent samples. I had understood the difference in location to be conventionally the difference in the sample medians however this is not the case when implemented in R. I have tied ranks and therefore non-exact p-value and confidence intervals are calculated due to the normal approximation. But what exactly is this

This is my first post to the mailing list and I guess it's a pretty stupid question but I can't figure it out. I hope this is the right forum for these kind of questions. Before I started using R I was using STATA to run a Wilcoxon signed-rank test on two variables. See data below:

Full_Name: Patrick Hodgson Version: 2.0 OS: solaris 2.9 Submission from: (NULL) (65.94.128.161) The value reported for the parameter W in the function wilcox.exact appears to be incorrect. I have checked the reference in the help file for this function (Myles & Hollander 1973, as well as 2nd ed. 1999 by same authors) and it is clear that W is the sum of the ranks of the data set with the

>>>>> Karolis Koncevi?ius >>>>> on Sat, 7 Dec 2019 20:55:36 +0200 writes: > Hello, > Writing to share some things I've found about wilcox.test() that seem a > a bit inconsistent. > 1. Inf values are not removed if paired=TRUE > # returns different results (Inf is removed): > wilcox.test(c(1,2,3,4), c(0,9,8,7))

Dear all, When we perform a Wilcoxon rank sum test (on two samples with different sizes) we get a test statistic. My question is, as the value of test statistic increases the difference between the distributions of the two samples also increase, right? Thanks in advance, João Fadista [[alternative HTML version deleted]]

Dear R-help, I have a question about pairwise.t.test and adjustment for multiple comparisons for paired data points. I have the following data: n=c("x", "x", "x", "x", "x", "x", "x", "x", "x", "x", "y", "y", "y", "y", "y", "y",

Hi UseRs, I don't want to die beeing idiot... I dont understand the different results between: cor() and cov2cov(cov()). See this little example: > x=matrix(c(0.5,0.2,0.3,0.1,0.4,NA,0.7,0.2,0.6,0.1,0.4,0.9),ncol=3) > cov2cor(cov(x,use="pairwise.complete.obs")) [,1] [,2] [,3] [1,] 1.0000000 0.4653400 -0.1159542 [2,] 0.4653400 1.0000000