similar to: Convergence problem in GLMM

Hello, I tried to compile v2.3.1 on Solaris x86 with SUN Pro compilers. I had an error while stats libarary was being compiled and I notice that "-xtarget=generic64" was not passed to f95 while cc used it. Could you tell me how to fix this problem? f95 -PIC -O -I/mounts/devel/SUNWspro/prod/include -c sgram.f -o sgram.o f95 -PIC -O -I/mounts/devel/SUNWspro/prod/include -c

Dear list, I have data on insect survival in different cages; these have the following structure: deathtime status id cage S F G L S 1.5 1 1 C1 8 2 1 1 1 1.5 1 2 C1 8 2 1 1 1 11.5 1 3 C1 8 2 1 1 1 11.5 1 4 C1 8 2 1 1 1 There are 81 cages and

Hello all. This may be a trivially simple question to answer, but I'm a little bit stumped with respect to the calculation of the F statistics in nested anovas in R. If I understand correctly, the F statistic for the among-subgroups but within groups hypothesis is calculated as MS_subgroups/MS_error, while the F statistic for the factor is calculated as MS_factor/MS_subgroups (I'm

Hi, I am performing a repeated measures 2-way ANOVA to assess the influence of plant and leaf on aphid fecundity. Fecundity is measured for each aphid on a single leaf. Here is what I typed. wingless <- reshape(Wingless, varying =

Lately R has been behaving strange on my Linux (Ubuntu 7.10) machine, with occasional segfaults. Today something else and reproducible happened: If I type the code below (meant for calibrating data), I get the error message that "the C stack usage is too close to the limit". calcurve <- cbind(1:2e4, 1:2e4, 1:2e3); #dummy curve, real one is more complex caldist <-

Dear all, I wrote the following batch script on a iMac, and ran it on a linux mosix cluster. tu <- read.table("cage.mm5.tags.rna_lib.CAA-CAJ.tu-reshape.table") tu_reshaped <- t(reshape(tu[1:50,], direction="wide", timevar="tu", idvar=c("rna","lib"))) write.table(tu_reshaped, "cage.mm5.tags.rna_lib.CAA-CAJ.tu-reshaped.table")

Hi, I am doing a binomial GLMM with a random intercept using the formula below, but I always get the same warning message. > m01 <- lmer(pres~ HT + DN + dtree + DNm + cmnhi + cmxes + cplan + craan + lfphal0100 + lfov0100 + lfop0100 + (1|plot), family=binomial, data=vphal, verbose=TRUE) 0: 6309.9448: 0.459924 -5.20747 -0.378722 0.558779 -0.200922 -0.0488451 -0.397844 0.367916 -2.09820

Dear All, I would like to ask you how to accomplish a little tricky data manipulation. I have a large dataset, looking something like: temp line cage number 18 18 1 6678.63 18 18 1 7774.458 18 18 1 7845.902 18 18 1 9483.578 18 18 1 8983.555 18 18 1 9181.052 18 18 1 9458.696 18 18 1 8138.616 18 18 1 7981.994 18 18 1 7556.491 18 18 1 7672.137 18 18 1 6607.776 18 18 1 8383.65 18 18 1 7129.852 18 18

Hi all, I am attempting to create a new variable based on values of other variables. The variable is called pharm. It basically takes the numeric code of 1 as yes and 0 to be No from the variable B20_C1 (a question on a survey). However, I would also like to have a level for non-respondents and these are captured in the variable nr.B20C, which is a 1 when there is a non-response on the whole group

Say we have a tab delimited file called bug.txt Part Rep Cage Hb pupae 1 1 S 32 1 M 34 L 42 2 S 36 M 28 L 36 read.delim("bug.txt") Part Rep Cage Hb.pupae 1 1 1 S 32 2 NA 1 M 34 3 NA NA L 42 4 NA NA NA 5 NA NA NA 6 NA 2 S 36 7 NA NA M 28 8 NA NA L 36 >

Dear All, I would like to ask a couple of questions on a LME model. I tested 4 selection lines at 4 food concentrations against a standard competitor stock. I had 3 replicate cages per selection line. In each cage I have 10 vials. I counted the number of wild type flies and competitor stock emerging in each vial. My main question is: is there any difference between selection lines? I did fit

Hi all, we have discovered a segfault in nsd-patch when renaming slave zone in nsd config file if some data for this zone still exists in the IXFR diff database. In my case, the zone "black" was renamed to "blackinwhite": > root at ggd115:/cage/nsd/var/nsd/zones#nsd-patch -c > /cage/nsd/etc/nsd-dns-slave.conf > reading database > reading updates to database >

On Nov 11, 2020, at 6:37 PM, Valeri Galtsev <galtsev at kicp.uchicago.edu> wrote: > > how do you map failed software RAID drive to physical port of, say, SAS-attached enclosure. With ZFS, you set a partition label on the whole-drive partition pool member, then mount the pool with something like ?zpool mount -d /dev/disk/by-partlabel?, which then shows the logical disk names in

Hi I am estimating the following coxph function with stratification and frailty?where each person had multiple events. m<-coxph(Surv(dtime1,status1)~gender+cage+uplf+strata(enum)+frailty(id),xmodel) ? > head(xmodel) id enum dtime status gender cage uplf 1 1008666 1 2259.1412037 1 MA 0.000 0 2 1008666 2 36.7495023 1 MA 2259.141 0 3 1008666

Hello, I have a problem concerning estimation of GLMM. I used methods from 3 different packages (see program). I would expect similar results for glmm and glmmML. The result differ in the estimated standard errors, however. I compared the results to MASS, 4th ed., p. 297. The results from glmmML resemble the given result for 'Numerical integration', but glmm output differs. For the

Dear R community, I have two questions regarding fitting GLMM using maximum likelihood method. The first one arises from trying repeat an analysis in the Breslow and Clayton 1993 JASA paper. Model 3 of the epileptic dataset has two random effects, one subject specific, and one observation specific. Thus if we count random effects, there are more parameters than observations. When I try to run the

Dear all, I'm puzzled by the behavior of stringHeight in the grid package. Consider the following test, library(grid) test <- function(lab="dog", ...){ g1 <- textGrob(lab) g2 <- rectGrob(height=grobHeight(g1), width=grobWidth(g1)) gg <- gTree(children=gList(g1,g2), ...) print(c("height:", convertUnit(stringHeight(lab), "mm",

Just installed stellarium-0.10.2-1.el6.rf(i686) last night with the Add/Remove Software tool. I'm getting video corruption and this message in the terminal: StelAppGraphicsScene: drawBackground needs a QGLWidget to be set as viewport on the graphics view A bit of Google work turned up this on the Ubuntu forum: "The new version of Stellarium 0.10.3 resolves my display problems.

Full_Name: Frank Beimfohr Version: 0.64.1, devel. OS: Solaris 2.5.1 Submission from: (NULL) (129.217.131.31) I try to compile R on my Sparc 4 (Solaris 2.5.1) but the compilation fails. I tried the developer-version and the contributed 0.64.1-Version. I start configure with the --g77-Option. During the compilation it stops with an error, which says that the R/src/library/modreg/src/bsplvd.f

Despite lots of investigation, I haven't found any R packages might be suitable for the following problem. I'd be very grateful for suggestions. I have three-way nested data, with a series of measures (obs) taken in quick succession (equal time spacing) from each subject on different days. The measures taken on the same day are temporally correlated, so I'd like to use an AR1