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Hi all, I am trying to set up a simple path analysis in the SEM package, but I am having some trouble. I keep getting the following error message or something similar with my model, and I'm not sure what I'm doing wrong: Error in solve.default(C) : system is computationally singular: reciprocal condition number = 2.2449e-20 In addition: Warning message: In sem.default(ram = ram, S = S,

Hello R users, When trying to fit a nonlinear mixed model to a respiration time series, I get the following error message: Error in recalc.varFunc(object[[i]], conLin) : dims [product 30] do not match the length of object [34] In addition: Warning message: In conLin$Xy * varWeights(object) : longer object length is not a multiple of shorter object length Below is an example that generates

We''ve run into an issue with an 8 node x3950 where xm info is showing only 6 nodes. I''ve traced the problem to the clip_to_limit function in arch/x86/e820.c. #ifdef __x86_64__ clip_to_limit((uint64_t)(MACH2PHYS_COMPAT_VIRT_END - __HYPERVISOR_COMPAT_VIRT_START) << 10, "Only the first %u GB of the physical memory map

Hope one of you could help with the following question/problem: We would like to explain the spatial distribution of juvenile fish. We have 2135 records, from 75 vessels (code_tripnr) and 7 to 39 observations for each vessel, hence the random effect for code_tripnr. The offset (‘offsetter’) accounts for the haul duration and sub sampling factor. There are no extreme outliers in lat/lon. The model

Testing on an 8-node 128-way NUMA machine has exposed a problem with Xen''s nr_cpus calculation. In this case, since Xen cuts off recognized CPUs at 32, the machine appears to have 16 CPUs on the first and second nodes and none on the remaining nodes. Given this asymmetry, the calculation of sockets_per_node (which is later used to calculate nr_cpus) is incorrect:

Dear R-ers, I am having trouble understanding why I am getting an error using glmmPQL (library MASS). I am getting the following error: iteration 1 Error in MEEM(object, conLin, control$niterEM) : Singularity in backsolve at level 0, block 1 The long story: I have data from an experiment on pairwise comparisons between 3 treatments (a, b, c). So a typical run of an experiment

I realized that I may not have answered the question you were asking and that no one else has responded. I can across a similar problem and may have an answer to your question now. If you have both the wavelet coefficients and the scaling coefficients then create a fake sequence of the same length as the original and decompose that sequence using wd form wavethersh with the same wavelet family

Hello! I was loooking in R-bugs and found under wishlist-fullfilled wish for "smart" placement of a legend. This has already been done in package gplots in function smartlegend. One question. This "bug-report" is under wishlist-fullfilled. Is it really fullfilled? Mail from Elizabeth --------------------------------------------------------------- It would be nice if

I am analysing some binary data with a mixed effects model using glmmPQL. I am aware that I cannot use the AIC values to help me find the minimum adequate model so how do I perform likelihood ratio tests? I need to fix on the minimum adequate model but I'm not sure of the proper way to do this. Thank you very much, Elizabeth Boakes Elizabeth Boakes PhD Student Institute of Zoology

I am analysing binomial data using a generalised mixed effects model. I understand that if I use glmmPQL it is not appropriate to compare AIC values to obtain a minimum adequate model. I am assuming that this means it is also inappropriate to use AIC values from lmer since, when analysing binomial data, lmer also uses PQL methods. However, I wasn't sure so please could somebody clarify

I am trying to run a GLMM on some binomial data. My fixed factors include 2 dichotomous variables, day, and distance. When I run the model: modelA<-glmmPQL(Leaving~Trial*Day*Dist,random=~1|Indiv,family="binomial") I get the error: iteration 1 Error in MEEM(object, conLin, control$niterEM) : Singularity in backsolve at level 0, block 1 >From looking at previous help

Hello all, I would like to perform SVM-RFE (Guyon et al. 2002) in R and have only found one implementation of this algorithm. The function belongs to the MCRestimate package but when I try to use it I encounter a problem - the function appears to be missing a required package or other function that I simply cannot find available anywhere. Here is my session info followed by a simple example

Full_Name: Elizabeth Purdom Version: 1.9.1 OS: Windows XP Submission from: (NULL) (171.64.102.199) It would be nice if names(obj) would give slot names as well. Since for many people slots are new, the first thing that happens is you try to access what's in them and can't find how to do it. If you don't know that slotNames() exists, it can be very frustrating. Moreover, if you

Hi, We have data of two groups of subjects: 32 elderly, 14 young adults. for each subject we have 15 observations, each observation consisting of a reaction-time measure (RT) and an activation maesure (betadlpcv). since we want to analyze the influence of (age-)group and RT on the activation, we call: lme(betadlpcv ~ RT*group, data=our.data, random=~ RT |subject) this yields: Error in

Full_Name: Elizabeth Purdom Version: 1.9.1 OS: Windows XP Submission from: (NULL) (171.64.102.199) It would be great if heatmap and/or image had the option of printing a legend bar on it somewhere that would indicate the ranges given by the colors in the heatmap (i.e. a very small image rectangle with the same colors as in the heatmap). Because heatmap is using layout, it seems pretty

The mirrorlist entry in my Fedora-11 /etc/yum.repos.d/fedora-update.repo reads: mirrorlist=https://mirrors.fedoraproject.org/metalink?repo=updates-released- f$releasever&arch=$basearch As far as I can see, this means that yum is looking for the file metalink at mirrors.fedoraproject.org ? If I try "sudo yum update" I get: ----------------------------------- [tim at elizabeth ~]$

Can anyone shed any light on this? > doubt.demographic.pql<-glmmPQL(random = ~ 1 | groupid/participantid, + fixed = r.info.doubt ~ + realage + minority + female + education + income + scenario, + data = fgdata.df[coded.resource,], + na.action=na.omit, +

Dear R users, I'm attempting to fit a GLM with random effects using the tweedie family for the error structure. I'm getting the error: iteration 1 Error in logLik.reStruct(object, conLin) : NA/NaN/Inf in foreign function call (arg 3) I'm running V2.1.0 I notice from searching the lists that the same error was reported in May 2004 by Spencer Graves, but no-one was able to

Hi all, I'm having some difficulty with lme. I am currently trying to run the following simple model anova(lme(x ~ f1 + f2 + f1:f2, data=m, random=~1|r1)) Which is currently producing the error Error in MEEM(object, conLin, control$niterEM) : Singularity in backsolve at level 0, block 1 x is a numeric vector containing 194 observations. f1 is a factor vector containing two levels, and