search for: unstructured

...spected >>> using the PST. >> >> Except loops that have multiple exits. they are not necessarily (single >> entry single exit) region, if the exists do not jump to the same exit bb. > > Yes, my assumption was to classify structured loops, but that does not exclude unstructured > regions that contain unstructured loops. Can you explain your definition of structured/unstructured loops/regions. A structured loop does have just one exit? Does a unstructured region have multiple exits, or it just contains unstructured code? Tobi

Hi, nlme users, I am fitting a model for repeated measures, using gls(). The var-cov structure is UNSTRUCTURED in lower triangle and identical for the diagonal, for which I still have no idea how to fit using PROC MIXED. The error message is as follows: Error in "coef<-.corNatural"(*tmp*, value = log((cStNatPar + 1)/(1 - cStNatPar))) : NA/NaN/Inf in foreign function call (arg 1) I ha...

Hi all. We are getting our first PRI line to use with Asterisk and one of the technical specifications is about framing, structured or unstructured. The main difference about them is almost clear for me: http://ckp.made-it.com/g704.html says: "G.704 is the framing specification for G.703. A carrier can 'steal' a 64kbps time slot (TS0) from a 2.048 Mbps line and use this to provide timing. The result is that 31 time slots are l...

...(resp. the line where the table starts)? 2. How do I break up each line to write the values into a matrix? Feel free to suggest an entirely different approach if you think that is helpful. Thanks a lot! Frauke -- View this message in context: http://r.789695.n4.nabble.com/extracting-data-from-unstructured-text-file-tp4464423p4464423.html Sent from the R help mailing list archive at Nabble.com.

...ry(geepack) geeglm(formula = Y ~ Year, id = TreeID, family = binomial, corstr = "exchangeable") #using waves. But I'm wondering if this is correct. library(geepack) geeglm(formula = Y ~ Year, id = PlotID, waves = TreeID, family = binomial, corstr = "exchangeable") #using a unstructured correlation on the plot level. geeglm with unstructured correlation resulted in an out of memory error. library(Zelig) zelig(formula = Y ~ Year, model = "logit.gee", id = "PlotID", corstr = "unstructured") #Ideally I think I need a correlation matrix structured like b...

On 01/08/10 14:20, ether wrote: > sorry that i forgot to change the subjuect > > > hi all, Hi ether, now a kind of more complete answer. > On 2010-1-7 0:11, John Mosby wrote: >> In LLVM we could add support for generalized CFG regions and >> RegionPasses. A region is a part of the CFG. The only information we >> have is, that it has one entry and one exit, this

...ngs that are resolved by the new analysis. - Why the current DivergenceAnalysis is broken - LLVM already includes a DivergenceAnalysis for GPU kernels. It is used in the GPU backends and to re-structure CFGs (StructurizeCFG pass). However, the existing DivergenceAnalysis of LLVM is broken for unstructured CFGs (bug report [9]): Example B: undetected divergence in unstructured control. entry:  divergent branch to B and C B:  uniform branch to C and D C:  %phi.var.hidden = phi .. <- undetected DIVERGENT phi  br D D:  %phi.var = phi .. <- detected DIVERGENT phi in IPostDom of entry  Ret T...

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I have a generalized linear model to solve. I used package "geepack". When I use the correlation structure "unstructured", I get a messeage that- R GUI front-end has stopped working. Why this happens? What is the solution? The r codes are as follows: a<-read.table("d:/bmt.txt",header=T") cutoffs<-c(1.75,3.34,5.09,6.93,9.11,11.8,15.3,20.1,23.7,27.3,30.9,34.3,37.6,41.5,46.5,51.1,57,63,73.1,93....

I am trying to write a function that will simulate observed counts X and Y as below, I want the function to be able give many replicates, can somebody advise? thanks Oarabile #alpha,n sdx and sdy are constant, and N is a vector of length n. unstructured<-function(n,N,alpha,sdx,sdy){ Vx<-rnorm(n,mean=0,sd=sdx) Vy<-rnorm(n,mean=0,sd=sdy) thetax<-exp(alpha+Vx) thetay<-exp(alpha+Vy) X<-rpois(n,N*thetax) Y<-rpois(n,N*thetay) data.frame(X,Y) } set.seed() unstructured() -- Mrs Oarabile Ruth Molaodi Department of Statistics and Mod...

...nd on the website for 5 or 10 minutes and I'm still not sure what this is. What is it? Why would I use it? What would I use instead of it? (Who are its competitors) When would I not use it? I see this "The software is a powerful and flexible solution that simplifies the task of managing unstructured file data", but I have no idea what "unstructured file data" means. -- ?Don't eat anything you've ever seen advertised on TV? - Michael Pollan, author of "In Defense of Food"

...ther the measures are related to certain covariates, and I have tried the generalised estimating equation function geeglm (library geepack) with the 'gaussian' family details like so: geeout <- geeglm(outcome ~ covariate1 + covariate2, id=familyID, family=gaussian, data=dat, corstr="unstructured") But I'm thinking that the limited range of the outcome violates the assumption of normality and that the results could be off. Q: Is there a way in R, either in geeglm or another appropriate function, to take the limited range of the outcome into account? Another aim of the analysis is...

Hello all, I'm kind of surprised that searching the archives and Googling haven't given me a result for this... I've got a large amount of data that is a good fit for CouchDB; it's reasonably unstructured, and such structure that exists is quite fluid. I want to slice the data in many different ways, some of which really don't fit well with a relational database model. I could probably do it using a relational DB, but it just doesn't feel like a good fit. What's the best way to go abou...

...crosstabulations as sparse matrices. I am using these in calculations for mixed-effects models and I understand that others may be interested in them for other applications. I would be happy to correspond off-list if you would like a preview of the capabilities. Metis is a package for partioning unstructured graphs, partitioning meshes, and computing fill-reducing orderings of sparse matrices. Although the entire source code for Metis is included in the Matrix package I am only using one of the functions for computing fill-reducing orderings. Perhaps those who are working on graphical models may want...

...1721 0 6 3 1 -0.4395021 1 7 4 1 -2.0944685 0 8 4 1 -1.8746840 1 9 5 1 -0.7784412 0 10 5 1 1.9952170 1 ... I am trying to use lme() to fit a relatively basic repeated measures model where there are random teacher intercepts, and an unstructured residual covariance matrix within students. The following call to lme() seems to fit the model: lme.t5<-lme(fixed=Y~time,data=d,random=~1|tchid,weights=varIdent(form=~1|time),\ correlation=corSymm(form = ~1|tchid/studid)) Now, I would like to try to alter this model to one in which the "...

..., I would like to fit a GLM model with GEE on clustered data. I tried to use gee in the GEE package on a twin data set. All cluster are of size 2. I removed the missing data and ordered by IDENTIF2 first. library(gee) mod.pc <- gee(Y ~ X1 + X2 , id = IDENTIF2, family = binomial, corstr = "unstructured", data = na.omit(df)) gives the following result : Beginning Cgee S-function, @(#) geeformula.q 4.13 98/01/27 running glm to get initial regression estimate (Intercept) X1M X2Sans AMP X2Stim -2.7756284 0.4658861 -1.6508288 -1.5059518 Erreur dans gee(Y ~ X1 + X2, id = IDENTI...

Hi! ? I have several mbox files (unstructured, only the big?plain mbox?files) and I would like to integrate/read these mbox files into mdbox subfolders of specific users.? This is a production system and I don't want to disturb running services and I am a bit afraid of not using the right command and maybe destroying (or whatever) their ma...

Hello, assume I have an "unstructured" text line from a connection. Unfortunately, it is in string format: R> x [1] "\talpha0\t-0.638\t0.4043\t0.4043\t-2.215\t-0.5765\t-0.137\t501\t2000" How can I extract the data included in this string object "x" in order to get the elements for the parameter vector cal...

...t I am observing differences between the three. The first model is a quasibinomial without any subject effects using glm. The second is a random-effects model using lmer. The third model is a generalized estimating equation using gee from the gee package in which I cluster for the subject using an unstructured correlation matrix. The results of the first and the third model almost coincide, but the second, using lmer, shows an insginficant coefficient where I would expect a significant one. The other 2 models show the coefficient significant. I do not really have experience with gee. Therefore I apologiz...

...defined covariance structure. I have my model y = xa +zb +e and b ~ N (0, C*sigma_square). (and a is a fixed effects) I would like to provide R the C (variance-covariance) matrix I can easily provide an example, but at this point I am first trying to know what is the best package the allows an unstructured covariance matrix. I was trying the function lme in the package nlme but I didn't have success in the defining the option "correlation" Thanks -- View this message in context: http://r.789695.n4.nabble.com/Mixed-Models-providing-a-correlation-structure-tp4635569.html Sent from the...