similar to: Samba as a domain member:

OK for the DC. I noticed that converting users and groups to sid with the example below seems to work fine: # wbinfo -n DOMAIN\\user S-1-5-21-948789634-15155995-928725530-6864 SID_USER (1) # wbinfo -n DOMAIN\\group S-1-5-21-948789634-15155995-928725530-11178 SID_DOM_GROUP (2) However, applications using PAM and winbind seem to fail when trying to convert to sid. For instance, just to name one,

Hi, my dependent variable is a proportion ("prob.bind"), and the independent variables are factors for group membership ("group") and a covariate ("capacity"). I am interested in the effects of group, capacity, and their interaction. Each subject is observed on all (4) levels of capacity (I use capacity as a covariate because the effect of this variable is normatively

Hello All, I have posted to this list before regarding the same issue so I apologize for the multiple e-mails. I am still struggling with this issue so I thought I'd give it another try. This time I have included reproducible code and a subset of the data I am analyzing. I am running an ANOVA with three factors: GROUP (5 levels), FEATURE (2 levels), and PATIENT (2 levels), where

Hi, I just get a question (sorry if it is a dumb one) and I "phase" my question in the following R codes: group1<-rnorm(n=50, mean=0, sd=1) group2<-rnorm(n=20, mean=1, sd=1.5) group3<-c(group1,group2) Now, if I am given a dataset from group3, what method (discriminant analysis, clustering, maybe) is the best to cluster them by using R. The known info includes: 2 clusters,

Dear list, I would like to do some calculation using different grouping variables. My 'df' looks like this: # Some data set.seed(345) id <- seq(200,400, by=10) ids <- sample(substr(id,1,1)) group1 <- rep(1:3, each=7) group2 <- rep(1:2, c(10,11)) group3 <- rep(1:4, c(5,5,5,6)) df <- data.frame(id, ids, group1, group2, group3) df <- rbind(df, df, df) df$time <-

Hi, For further calculations I need to extract indivdual Variances of different random effects from a fitted model. I found out how to extract the correlations (VarCorr(m1)@reSumry$group1) but I was not able to find a way to extract the other components individually. To extract the Residuals I tried: (ranef(m1)@ stdErr) which unfortunately did not work. Thank you very much for your help!

Dear all, First, let's create some data to play around: set.seed(1) (df <- data.frame(Group=rep(c("Group1","Group2","Group3"), each=10), Value=c(rexp(10, 1), rexp(10, 4), rexp(10, 10)))[sample(1:30,30),]) ## Now we need the empirical distribution function: edf <- function(x) ecdf(x)(x) # empirical distribution function evaluated at x ##

Is there a way of positioning the color key in levelplot when the axes are on a categorical (rather than numerical) scale? I've put some sample code below. I need to add a secondary y axis to the right side of my plot but then the labels interfere with the color key (which is currently on the right side). Is there a way to shift the color key over a bit more to the right? I've tried

Dear list, I am confused on how to explain the interaction term in the context of "treatment contrast". for example, I have an data frame as below: sub group val 1 a group1 3.685625 2 a group1 3.407445 3 a group1 4.040920 4 a group1 2.890875 5 b group1 3.853280 6 b group1 4.113585 7 b group1 3.043250 8 b group1 3.800920 9 c group1 5.394305 10 c

Hi all, I'd appreciate any pointers or advise regarding the following issue with files written by M$ Office on Samba 3.0.32 on snv_98 (OpenSolaris) on a ZFS filesystem: samba share: [sharename] read only = No browseable = yes writeable = yes directory mask = 0770 create mask = 0770 delete readonly = Yes acl check permissions =

Hello, unfortunately, I don't know a better subject. I would like to be very flexible in how to process my data. Assume the following dataset: par1 <- seq(0,1,length.out = 100) par2 <- seq(1,100) fac1 <- factor(rep(c("group1", "group2"), each = 50)) fac2 <- factor(rep(c("group3", "group4", "group5", "group6"), each =

Dear friends, My R*C table is as follow: better good bad Goup1 16 71 37 Group2 0 4 61 Group3 1 6 57 Can I test if there are statistical significant between Group1 and Group2, Group2 and Group3, Group1 and Group2, taking into the multiple comparisons? The table can be set up using the following program: a<-matrix(data=c(16,71,37,0,4,61,1,6,57),nrow=3,byrow=TRUE) Thanks

Hello All, I'm deploying NUT in a data center and I'm curious to know how others have gone about staging the shutdown of various systems. The systems are broken down into groups of importance, group1 being the most important group4 being the least. In the event of an outage take down group4 after 5 minutes, group3 after 10 minutes, group2 after 15, and finally group4 after 20. I've

If I have 3 groups,and for each group,I get the ratio(e.g. incidence rate). Now I wanna compare 3 ratio pairwise,and get the corresponding p values,i.e: group1 vs group2 ,p value=? group1 vs group3 ,p value=? group2 vs group3 ,p value=? Which statistical test should be used? Thanks a lot for your help. [[alternative HTML version deleted]]

I maintain a directory structure containing dirs and files that I regularly push to ~50 hosts, which are divided into 3 groups that have slightly different needs (minor mods in a couple of files). So ideally I would have 4 directories: /path/to/sync/common/ <- common files /path/to/sync/group1/ <- group1 specific only /path/to/sync/group2/ <- group2 specific only

Hello While searching the archives and googling for : -login script to map drives according to group membership I saw lots of complicated solutions (on-the-fly scripts, group directories) etc. but the following works very well for me: I downloade dthe ifmember.exe from the microsoft website, and stuck it in the netlogon directory (not the scripts directory)

Hello, i got a msdfs share running and now i want to hide folders from users who got no access to them anyway. For example: List of shares: test1 test2 User sees only: test1 Is something like that possible mit samba itself or does someone know a workaround to get it running like that ? Thanks for any ideas. A.Dura

Dear List, I am looking to perform exploratory analyses of two (relatively) large datasets of categorical data. The first one is a binary 80x100 matrix, in the form: matrix(sample(c(0,1),25,replace=TRUE), nrow = 5, ncol=5, dimnames = list(c( "group1", "group2","group3", "group4","group5"), c("V.1", "V.2", "V.3",

I'm having trouble with files being marked read-only in Windows because the Solaris file owner does not have write-permissions on the file; group-write is allowed: -r--rw---- 1 user group 32 Feb 13 14:19 testfile.txt I thought that setting "store dos attributes = yes" for this share would allow the "read only" setting to be stored in extended attributes, but it

Hello All, i am repeating this question for the sixth time but i think i was not explaining the problem correctly. ............. Now i will try to explain it...... I have 4 telephone lines(PSTN) in my PBX. Now I want to make groups of the extensions to use that lines. e.g. extensions 12,13 & 31 are in groupA extensions 14 - 20 are in groupB extensions 21 - 30