similar to: Column order in stacking/unstacking

Hi I have multi domain environment with root domain and subdomain. Forest and domain level windows 2003 native. Also forest prep and domain prep did for sccm 2007 ocs 2007 and Exchange 2003. After join Samba to domain like ad dc I had some problem with replication: ################################################# [root at dc03 ~]# samba-tool drs replicate dc02 dc03

Am Sa., 6. Apr. 2019 um 18:01 Uhr schrieb Rowland Penny via samba < samba at lists.samba.org>: > On Sat, 6 Apr 2019 17:21:26 +0200 > Martin Krämer <mk.maddin at gmail.com> wrote: > > > Hello Rowland, > > > > thanks for your help. > > Below my comments > > > > See here: > > > > > > http://apt.van-belle.nl/ > > >

Hi Everyone, I am trying to understand the unstack() function but after struggling for two days, I have given up. More specifically, I am trying the exercises at the end of Chapter 1 of Data Analysis and Graphics Using R by Maindonald and Braun, 2nd ed. Exercise 18 (p. 41) asks to unstack the Rabbit data frame from the MASS package to get a certain data frame that is shown in the exercise.

Quick question: Which function do you use to calculate partial derivatives from a model equation? I've looked at deriv(), but think it gives derivatives, not partial derivatives. Of course my equation isn't this simple, but as an example, I'm looking for something that let's you control whether it's a partial or not, such as: somefunction(y~a+bx, with respect to x,

Is the labeling/naming of levels in the documentation for the predict.glmmPQL function "backwards"? The documentation states "Level values increase from outermost to innermost grouping, with level zero corresponding to the population predictions". Taking the sample in the documentation: fit <- glmmPQL(y ~ trt + I(week > 2), random = ~1 | ID, family =

Hola a todos, Necesito estimar dos parametros utilizando la función nlm; fit<-nlm(hood2par,c(x01[i],x02[j]),iterlim=300, catch=x[,c(3,4,5)],sp=.5) donde hood2par es una logística modificada. Pero en mi caso, la convergencia de nlm depende de los valores iniciales de dichos parámetros. Para buscar dichos valores iniciales de manera automática, genero dos vectores de valores iniciales

Dear R-List, I would like to recode my data according to quantile breaks, i.e. all data within the range of 0%-25% should get a 1, >25%-50% a 2 etc. Is there a nice way to do this with all columns in a dataframe. e.g. df<-

One would normally want the original order that so that one can stack a list, operate on the result and then unstack it back with the unstacked result having the same ordering as the original. LL <- list(z = 1:3, a = list()) # since we can't do s <- stack(LL,. drop = FALSE) do this instead: s <- transform(stack(LL), ind = factor(as.character(ind), levels = names(LL))) unstack(s)

Dear R-List, I am sure there must be a very simple way to do this - I just do not know how... This is what I want to do: #my dataframe df<-data.frame(id=c("x01","x02","x03","x04","x05","x06"),a=c(1,2,NA,4,5,6),b=c(2,4,6,8,10,NA),c=c(NA,3,9,12,NA,NA),sum=c(3,9,15,24,15,6))    id    a     b     c   sum 1 x01  1     2    NA   3 2

Am 13.03.19 um 18:50 schrieb Rowland Penny via samba: > Try running 'samba-tool ldapcmp ldap://dc1 ldap://dc2' thanks! I get differences, too many to post here, but I assume mostly related to the drift between the 2 dcs now? (lastLogonTimestamp seems obvious to me) What might solve the initial problem *maybe* * Comparing [DNSFOREST] context... * Objects to be compared: 19

I've been reading the R mail archives and I've found a lot of messages with this same kind of problem, but I can't understand the answers. Can one of you try to explain this to me? Here's my example. Given a regression model and a variable, I want to use unstack() on the vector of residuals and make some magic with the result. But unstack hates me. PCSE <- function

When converting from a single transaction to a linked list, I forgot to free the storage for each member of the list. Reported-by: Richard W.M. Jones <rjones at redhat.com> Fixes: 7f5bb9bf13f041ea7702bda557d9dd668bc3423a Signed-off-by: Eric Blake <eblake at redhat.com> --- I'm still not sure why 'make check' passes while 'make check-valgrind' fails for

Hi, I am trying to plot several rows out of a list of thousands. I have 40 columns, and about 16,000 rows with the following Df structure. ID X01 X02 X03..X40 AI456 45 64 23... AI943 14 3 45 .. AI278 78 12 68.. BW768 -2 -7 34.. ... My question is, I have a list of 100 IDs generated elsewhere (Df-"Ofinterest"), I would like to plot the 100 IDs from that data frame over the 40 columns

Folks, I have the following dataframe: > x <- structure(list(name = c("EU B", "EU B", "EU B", "EU B", "EU B", "EU B", "AU A", "AU A", "AU A", "AU A", "AU A", "AU A"), date = c("2010-10-11", "2010-10-12", "2010-10-13",

Hello, I came across a problem when building a randomForest model. Maybe someone can help me. I have a training- and a testdataset with a discrete response and ten predictors (numeric and factor variables). The two datasets are similar in terms of number of predictor, name of variables and datatype of variables (factor, numeric) except that only one predictor has got 20 levels in the training

Say I have the following data: testDat <- data.frame(A = c(1,NA,3), B = c(NA, NA, 3)) > testDat A B 1 1 NA 2 NA NA 3 3 3 rowsums() with na.rm=TRUE generates the following, which is not desired: > rowSums(testDat[, c('A', 'B')], na.rm=T) [1] 1 0 6 rowsums() with na.rm=F generates the following, which is also not desired: > rowSums(testDat[, c('A',

Am 13.03.19 um 17:13 schrieb Stefan G. Weichinger via samba: > Am 13.03.19 um 16:53 schrieb L.P.H. van Belle: >> Ok thats small, a dc should be rebooted within 1-2 min and 1-2 min really max for AD sync. one more observation: manually running this works: root at pre01svdeb03:~# samba-tool drs replicate dc PRE01SVDEB03 dc=blabla,dc=at --full-sync but the one user I created (and

R-helpers, Below is a simple example of some output that I am getting while trying to work with a data frame in R 2.12.1 for Mac. ----- > testdat <- data.frame(matrix(ncol=10, nrow=10)) > colnames(testdat) <- c('a','b','c','d','e','f','g','h','i','j') > testdat[seq(1,10,3),] <-

Hi folks, I am new to the list and relatively new to R. I am trying to unstack data "arraywise" and could not find a convenient solution yet. I tried to find a solution for the problem on help archives. I also tried to use the reshape command in R and the reshape package but could not get result. I will illustrate the case below, but the real dataset is quite large so that I would

We?ve been seeing this a lot lately on generic CentOS 6 rpm installs: rpm -qa | grep libguestfs libguestfs-java-1.16.19-1.el6.x86_64 libguestfs-java-devel-1.16.19-1.el6.x86_64 libguestfs-1.16.19-1.el6.x86_64 libguestfs-tools-1.16.19-1.el6.x86_64 libguestfs-javadoc-1.16.19-1.el6.x86_64 libguestfs-devel-1.16.19-1.el6.x86_64 libguestfs-tools-c-1.16.19-1.el6.x86_64