similar to: Collapsing data frame; aggregate() or better function?

I wrote a simple log likelihood (for the ordinary least squares (OLS) model), in two ways. The first works out the likelihood. The second merely calls the first, but after transforming the variance parameter, so as to allow an unconstrained maximisation. So the second suffers a slight cost for one exp() and then it pays the cost of calling the first. I did performance measurement. One would

summary: The function 'by' inconsistently strips class from the data to which it is applied. quick reason: tapply strips class when simplify is set to TRUE (the default) due to the class stripping behaviour of unlist. quick answer: This can be fixed by invoking tapply with simplify=FALSE, or changing tapply to use do.call(c instead of unlist executable example:

Dear List, I have a logical data frame with NA's and a grouping factor, and I want to calculate the % TRUE per column and group. With an indexed database, result are mainly limited by printout time, but my R-solution below let's me wait (there are about 10* cases in the real data set). Any suggestions to speed this up? Yes, I could wait for the result in real life, but just curious if I

I would like to put confidence intervals on a mantel corellogram they are already calculated in the pmgram object but I am unsure how I get the x value in order to plot them? package(ecodist) X<-1:100 Y<-rnorm(1:100) Z<-rnorm(1:100) XY<-dist(data.frame(X,Y)) YX<-dist(data.frame(Y,X)) my.mgram<-mgram(XY,XZ) plot(my.mgram) print(my.mgram) > print(my.mgram) $mgram

Hi We have an all SAMBA Domain (all samba-3.0.23d) running with two OpenLDAP servers (2.3.27). We experience quite a few NT_STATUS_IO_TIMEOUTs when using smbclient. Windows clients just experience delays (up to several minutes). I've done some debugging: On the client i issue: smbclient -Umhansen //lfs1/mhansen lfs1 is a domain member server. On lfs1 (log level 10) i get the following in

Andr?, are you quite sure you have it working? In this thread someone from Open-Xchange stated that no, Dovecot doesn?t have SMTPUTF8 support implemented, and the same response was given by another Dovecot developer last September (it ?is being considered? was the answer then, see https://dovecot.org/pipermail/dovecot/2018-September/112887.html). I am using LMTP to deliver mail to Dovecot from

On 05/04/2019 08:57, David B?rgin via dovecot wrote: > Andr?, are you quite sure you have it working? > > In this thread someone from Open-Xchange stated that no, Dovecot doesn?t > have SMTPUTF8 support implemented, and the same response was given by > another Dovecot developer last September (it ?is being considered? was > the answer then, see >

Howdy R gurus ! I am newbie to R I use R 2.0.1 in Windows XP. When I run R I got the follwoing memory error. My physical memory size is 3 Gb. My R got the memory problem when it reached to about 2 Gb. Thanks in advance, > library(spdep) > sfr.lagsarlm <- lagsarlm(sfr.data$Bldgsqft ~ sfr.data$Ncounty + sfr.data$Nugb + sfr.data$Ngroup, data=sfr.data, listw=sfr.listw,

Hi I have a problem with subject. I have a samba 3.0.1 server to which both windows and linux (using smbclient version 3) users can connect perfectly. But smbclient version 2.2.8a or earlier users cannot connect to this server. I have searched release notes, changelogs, the linux.samba newsgroup and found no indication of others having the same problem. Most likely it is something I have

Hi, I'm running Samba 3.0.11 on RedHat ES 3 kernel version 2.4.21-15.0.4.ELsmp and have a quick question about AD group membership limits Am I right in assuming that Samba is limited by the group membership parameters (ie NGROUP = 32) imposed by the Linux kernel? Is there any workaround in Samba for this? At the moment if a user is a member of more then 32 domain groups they cannot access

On 2019-04-05 08:57, David B?rgin via dovecot wrote: > Andr?, are you quite sure you have it working? > > In this thread someone from Open-Xchange stated that no, Dovecot > doesn?t > have SMTPUTF8 support implemented, and the same response was given by > another Dovecot developer last September (it ?is being considered? was > the answer then, see >

Dear R-users, I am facing problem with integrating in R a likelihood function which is a function of four parameters. It's giving me the result at the end but taking more than half an hour to run. I'm wondering is there any other efficient way deal with. The following is my code. I am ready to provide any other description of my function if you need to move forward.

Seems crossval from library(bootstrap) can only be used for leave-one-out and k-fold cross validation? Here is a dumb question, suppose n=80, how to do exactly leave-50-out cross validation? K-fold cross validation is not eligible for this case since n/ngroup is not an integer. Thanks!

The Fedora build system is in paranoid mode, and compiles everything with -Werror. Additionally, it checks that the return values of calls like read and write are checked. The build exits with errors like: xen/lowlevel/xc/xc.c: In function `pyxc_vmx_build'': xen/lowlevel/xc/xc.c:464: warning: ignoring return value of `sscanf'', declared with attribute warn_unused_result

Dear R users, I am sorry to disturb you! But I really need your help for the usage of sigPathwy. Actually, I want a sliding window analysis for possible chromosome expression pattern mining. My research microorganism is a plant pathogen, Gibberella zeae, and I first used SAS to divide locus number with 10, 20, 30, or 40 on the fungal chromosome according to their location. I really

A few problems in R-0.50-a3 (which were also in R-0.49): 1) y <- c(10,11,12,13,14,NA,NA) n <- length(y) missed <- (1:n)[is.na(y)] notmissed <- (1:n)[!is.na(y)] blocks <- cut(missed,breaks=c(0,notmissed,n+1)) a <- function(v) { q <- range(v) c(q[1]-1,q[2]+1) } brackets <- tapply(missed,blocks,a) This codes gives the following in S: > brackets $"0+ thru 1":

Hi- I want to fit a model with crossed random effects and heteroskedastic level-1 errors where inferences about fixed effects are of primary interest. The dimension of the random effects is making the model computationally prohibitive using lme() where I could model the heteroskedasticity with the "weights" argument. I am aware that the weights argument to lmer() cannot be used to

Though tapply(x, factor, fun, simplify =TRUE) should be equivalent to sapply(split(x, factor), fun, simplify=TRUE), note simplify=TRUE, it is not so if fun() returns a vector rather than a scalar, e.g. > tapply(1:6, c(0,0,0,1,1,1), function(x) c(min=min(x), max=max(x)), simplify=TRUE) $"0" min max 1 3 $"1" min max 4 6 > sapply(split(1:6, c(0,0,0,1,1,1)),

The function tapply is not working in the Windows version of R=20 (Version 0.50 Beta (Sept 29, 1997)) In tapply <- function (x, INDEX, FUN=3DNULL, simplify=3DTRUE, ...)=20 ... The part: if (simplify && all(unlist(lapply(ans, length)) =3D=3D 1)) { ans <- unlist(ans, recursive =3D FALSE) names(ans)<-namelist[[1]] return(ans) } should be replaced by if (simplify

Hello, I am trying to figure out if there exists some R command that allows one to be particularly selective when reading a file. I'm dealing with large fixed-width data sets that look like 539001.. 639001.. 639001.. ... 539002.. 639002.. ... Presently, I am using read.fwf to read an entire file, but I am interested only in reading those records beginning with 5. I have been unable to