search for: nmle

Dear R users, I'm applying a correlation structure in a mixed model (nmle function) to control for spatial correlation between land parcels that are adjacent to each other. I generated X,Y coordinates in ArcGIS for each land parcel and used them in the correlation form like this: test.exp<-corExp(1, form = ~ X + Y) test.exp<- Initialize(test.exp,dataset) However...

Following the Indomethicin example in Pinheiro & Bates, chapter 6, page 277 etc, coming to the following comand: fm2Indom.nlme <- update( fm1Indom.nlme, random = pdDiag(A1 + lrc1 + A2 ~ 1) ) debugging nlme gives the following output: Browse[1]> n debug: modelResid <- ~eval(model, data.frame(data, getParsNlme(plist, fmap, rmapRel, bmap, groups, beta, bvec, b, level,

Hi I am using R 1.7.1 on RH linux 9.0 > sum(unlist(lapply(ls(),function(x)object.size(get(x)))))/1024^2 [1] 2.424263 so I am not using much memory (I have a gig of ram on my machine) now in nlme > gtest<-groupedData(log(X8)~Time|sub,all[,c(names(all)[1:9],"X8")],outer=~A*B) > object.size(gtest)/1024 [1] 59.98438 > plot(gtest,outer=~Dose*chem,key=FALSE,asp=.5) Plotting

Hello. I have 16 subjects with 1-4 obs per subject. I am using the package "nlme" to fit a simple random effects (variance components model) with 3 parameters: overall mean (fixed effect), between subject variance (random) and within subject variance (random). I need a 3x3 variance-covariance matrix that includes all 3 parameters in order to compute the variance of a specific

Hi, All: Does 'nlme' require the nonlinear function to be differentiable? I'm fitting structural change models to many related time series, and I'd like to improve the estimates of the change point times through some type of pooling. Unfortunately, I've so far been unable to get 'nlme' to work for me. The following toy example is the closest I've come

A few days ago I posted a question to this discussion group concerning to origin of an error message < subscript out of bounds > while using the nonlinear mixed model (nlme) function in R with a self-starting function. Thanks for those who responded. This posting is to explain what (I think) it causing the error. Pinheiro & Bates (2000, pages 342-347) describe how to construct a

Hi, I am not sure this is a bug but I can repeat it, The functions and data are below. I know this is nasty data, and it is very questionable whether a 4pl model is appropriate, but it is data fed to an automated tool and I would have hoped for an error. Does this repeat for anyone else? My details: > version _ platform i686-pc-linux-gnu

...e? For example, if I want to make a new data frame that only includes rows of data for which the p values (given by one of the columns in the data frame) are less than a certain value, how do I do this? It seems that there should be a simple function that does this. I looked into getGroups from the nmle package, but am not sure how to construct the form argument correctly or even if it's the appropriate way to tackle this. Thanks in advance of your answer, Matt

...mpressed with it's package handling as well as the gui. So I tried to see what was due for update and packages such as Hmisc, Matrix and others came up. But when I had updated them - which took a few goes as something hung between here and Bristol - I noticed that the default packages such as nmle, MASS had disappeared. I re-installed them but is this a glitch or a feature? Best wishes John John Logsdon "Try to make things as simple Quantex Research Ltd, Manchester UK as possible but not simpler" j.logsdon at quantex-research.com...

I'm trying to set up a mixed model to solve using lme. It will have 3 fixed effects, two random effects and two interaction terms. I've been reading Pinheiro's and Bates's book on the nmle library, but find the part about display functions to be unclear. When creating a groupedData object from a data.frame, you need to enter a function of the form: response ~primary|grouping Does this display function serve any purpose later on when specifying the model in the call to lme? If s...

...package only allows me to model variance covariance information for random effects. What I am interested in is to actually specify a variance covariance matrix of the residuals within year that would describe the unexplained spatial dependence of the errors within each year. I had a look at the nmle pack in Splus and it appears that the nmle function in that package is able to describe such a var-covar matrix via the var.function option. So I was wondering if lmer can do that in R. I also looked at the MCMCpack in R since I might decide to actually use Bayesian modeling when using m...

...: Windows XP Submission from: (NULL) (66.93.61.221) BIC() requires the attribute $nobs from the logLik object but the logLik of a glm(formula,family=binomial()) object does not include $nobs. Adding attr(obj,'nobs') = value, seems to allow BIC() to work. Reproducing the problem: library(nmle); BIC(logLik(glm(1~1,family=binomial())));

...e F-values as 8V does. Though the R computations thrash my system (FreeBSD, K6-233, 64MB). I have to triple the swapspace before starting, and I wait about an hour for either rebooting the system or having a lucky outcome. There seems to be something fundamentally wrong. It seems I have to move to nmle to get variance components. I did not manage to translate my problem to mle language yet. Thanks for any help -- Dipl.-Math. Wilhelm Bernhard Kloke Institut fuer Arbeitsphysiologie an der Universitaet Dortmund Ardeystrasse 67, D-44139 Dortmund, Tel. 0231-1084-257 -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-....

I'm using the lme function in nmle to estimate the variance components of a fully nested two-level model: Y_ijk = mu + a_i + b_j(i) + e_k(j(i)) lme computes estimates of the variances for a, b, and e, call them v_a, v_b, and v_e, and I can use the intervals function to get confidence intervals. My understanding is that these inter...

...200), verbose=TRUE, method="REML", na.action=na.pass) this fit give the following error: Error in MEEM(object, conLin, control$niterEM) : Singularity in backsolve at level 0, block 1 HOWEVER, in SAS the same model with covariate is WORKING! When I'm changing the fixed part in nmle as follows fixed=list(A0+Ea~1,A1~1|Process), then the following error is popping up: Error in contr.treatment(n = 0L) : not enough degrees of freedom to define contrasts In addition: Warning messages: 1: In Ops.factor(1, Process) : | not meaningful for factors 2: In Ops.factor(1, Process) : |...

...9;m afraid that's because my previous question was too vague. Let me try again with a more specific question, and I hope someone can help. NOTE, I know I should be using the newer lme4 package, I just haven't had a chance to update my version of R yet, so the question below relates to nmle. I have data from a classical quantitative genetics experiment, with 33 sires mated each to 2 dams, with 15 progeny from each dam raised on 5 host plants (3 larvae per host). So the model I would like to run has the following factors: Host (fixed) Sire (random) Dam [nested within sire] (random...

...RAN" was detected? I know there has been discussion in the past about how to have a package not do things like run long tests when on CRAN ... I think CRAN maintainers would probably notice an attempt at typosquatting on a common package (e.g. "ggplot" for "ggplot2", "nmle" for "nlme"), but again I'm not sure ...) 2. The feasibility to achieve code execution upon package installation on the host system. [I think this one is true, due to the possibility of including a generic Makefile?] I've pasted the author's comments about defense be...

...t ~ direct * flicker *ground *retest +person + Error( person : ( direct * flicker *ground *retest ))) Indeed, summary(latm.aov) gives the same F tests than BMDP8V for the 1st part of the evaluation. But I don't get variance components from this. So it looks as if I have to change to mle from nmle package. I did not succeed to translate this model to mle yet. Trial-and-error fails mostly, because the problem thrashes my system (FreeBSD, K6-233, 64MB). This is particularly astonishing, as BMDP8V does it's work without problems on an old 24MB uVAX VMS system in mere 20 seconds CPU time. T...

Dear R users, Being a R-novice using version 1.7.0 I have not managed to solve the following problem, so I turn to you: I have 12 pairs nonlinear curves having some parameters (p1,p2,p3) in common and others specific to one of the curves (p4a,p4b). I want to fit a nonlinear mixed model with nmle with the random effects varying over the 12 samples (pairs). In order to be able to estimate the parameters, the two curve pairs must be analyzed/fitted simultaneously. Do you have any suggestions on hov to proceed? Sincerely A. Frigyesi Lund, Sweden excerpt from data: pd pa...

...libs aren't on the system, by all the .so lib files for each of those listed above are installed]. Serious pain in the butt. R 3.2.5 was working perfectly -- upgrade pretty much gummed things up, as far as compiling some packages. What I don't understand is -- wouldn't packages like nmle (which are core packages in R) be configured for your specific RHEL distribution to have dependencies that are compatible? Either that, or I'm missing something completely. Thanks in advance.