similar to: nlminb doesn't converge and produce a warning

Hi Everyone, Can anyone help me resolve a problem that i'm having with nlminb. The problem is that it stops after just one iteration and returns the same values as "start" ones. Thank you very much for your help. Sincerely. -- Kamel Gaanoun (+33) (0)6.76.04.65.77 [[alternative HTML version deleted]]

Hi Everybody, please can you help me how to call BayesX in R in order to see the graph already exist in BayesX Thanks ---------- Forwarded message ---------- From: <r-help-request@r-project.org> Date: Sat, Jan 22, 2011 at 5:00 AM Subject: R-help Digest, Vol 95, Issue 22 To: r-help@r-project.org Send R-help mailing list submissions to r-help@r-project.org To subscribe or

hi i have the following dataframe x y 1 345 6 NA 8 123 32 123 12 NA 6 124 7 NA and i want to extract the data rows which contains "NA" data, I tried subset(dataframe,y=="NA") but fail. if you know the answers, please let me know thanks. typhoong -- View this message in context: http://r.789695.n4.nabble.com/Extract-NA-data-rows-tp3235568p3235568.html Sent from the

VM traffic is already limited by a throughput limit, but there is no control over the maximum packet per second (PPS). In DDOS attack the major issue is rather PPS than throughput. With provider offering more bandwidth to VMs, it becames easy to coordinate a massive attack using VMs. Example: 100Mbits ~ 200kpps using 64B packets. This patch provides a new option to limit VMs maximum packets per

"CALL FOR PAPERS" THE ISLAMIC SOCIETY IN SOUTH EAST ASIA CONFERENCE ON STATISTICAL AND MATHEMATICAL SCIENCES BANDUNG, 25 - 26 APRIL 2003 Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Islam Bandung Jalan Tamansari No. 1, Bandung 40116 Telepon +62 22 4203368 Ext. 136 or 135 Facsimile +62 22 4263895 E-mail: - fmipa_unisba at yahoo.com - wanda at

Hello R users, I'm trying to do simulations for comparing cox and weibull I have come across this problem: Warning messages: 1: In survreg.fit(X, Y, weights, offset, init = init, controlvals = control, : Ran out of iterations and did not converge 2: In survreg.fit(X, Y, weights, offset, init = init, controlvals = control, : Ran out of iterations and did not converge what i did is

Hello All,   I¢m  kinda new to R language and any help that I can get is greatly appreciated.   Basically, I want to find the values of the two parameters that will maximize the function and I¢m currently using the optim function to find these values.  My R code works fine but not all the time.  Sometimes the solution converges, sometimes not.   Since I¢m planning to do this 5000 times, is there a

Dear all, I need to know in which number of iterations the kmeans converge each time I run it. Any idea how to do it? Thank you for your attention, Rui

Help! Being a bit of a novice, please bear with me if this is a stupid question! I am trying to fit a saturated model to some count data that I have: model<-glm(COUNT~SP*LOC*COL*TIME*TREAT,poisson) but R keeps on crashing and coming up with (occasionally before crashing) an error that states: Algorithm did not converge in: (if(is.empty.model(mt)) glm.fit.null else glm.fit)(x = X, y = Y,

After running a model for a while and seeing that it did not converge yet, how can I continue to run, ie not starting anew, the model? I know if I manually/interactively use winbugs, this is possible anytime, but how can I do this in r2winbugs, so that my existing sim$sims.array and other stuff in the object that bugs() returns gets extended? Thanks Toby

When I ran a Gamma regression in SAS, the algorithm converged. When I ran it in R, it keeps uncoverged even if I used 10000 iterations. What was wrong? I used the following code in R: glm(y ~ x1 x2 x3, control=glm.control(maxit=10000), data, family=Gamma(link="log")) [[alternative HTML version deleted]]

Hi All, I run function "kmeans" to cluster a matrix. But when the matrix size is big enough, it keeps saying "did not converge in 10 iterations". Could you explain what it means and if the result is wrong? And the interesting thing is sometimes this warning happens when the sample size is around 51200 x 6, sometimes it happens around 30000 x 6. Does the warning related

Running the Chapter 4 examples in Pinheiro & Bates' "Mixed-Effects Models in S and S-PLUS" (2000), I get a message that the default optimizer doesn't converge, but using "optim" for the optimizer results in convergence: > > library(nlme) > > fm1IGF.lis <- lmList(IGF) > > fm1IGF.lme <- lme(fm1IGF.lis) > Error in lme.formula(fixed =

I have a set of functions: Probability <- function(N, f, w, b, l, n, q) { #N is the number of lymph nodes #f is the fraction of Dendritic cells (in the correct node) that have the antigen #w is time in terms of hours #b is the starting position (somewhere in the node or somewhere in the gap between nodes. It is a number between 1 and (x+t)) #q is the length of the time step #l is the LN

Dear all, I am working on a data set in which I have sequentially measured egg temperatures ("eggtemp") in birds incubating in different ambient temperatures ("treat", sample data set below), "id" is not replicated within treatment. id treat eggtemp 1 79 3 30.90166 2 42 3 34.94044 3 10 3 32.69945 4 206 3 36.64127 5 23 3 31.80055 6

Dear all, I'm building binomial mixed-model using lme4 package. I'm able to obtain outputs properly except when I include two particular variables: date (from 23 to 34; 1 being to first sampling day) and Latitude (UTM/100 000, from 55.42 to 56.53). No "NA" is any of those variables. In those cases, I get the warning message: "nlminb failed to converge" I tried to

I am using the Ben bolker's R package "bbmle" to estimate the parameters of a binomial mixture distribution via Maximum Likelihood Method. For some data sets, I got the following warning messages: *Warning: optimization did not converge (code 1: ) There were 50 or more warnings (use warnings() to see the first 50)* Also, warnings() results the following: *In 0:(n - x) : numerical

Hi, So for awhile I have been seeing this issue but it hasn''t been painful. However, recently I have been deploying a new module that has made it much more annoying. file { cdh3_config: recurse => true, ignore => ".svn", checksum => md5, notify => Exec[hadoop_alternatives], require

Hello R users, I am trying to minimize two functions with genoud. It is actually one function with two sets of data, each of them having two unknown variables (called Vcmax and gi) which have the same value in each of the function. They are called f.1 and f.2 in the code below. My objective to minimize the functions in order to get the two variables equal in each of the functions. Furthermore, I

Someone can help me? I tried several things and always don't converge # Model library(sem) dados40.cov <- cov(dados40,method="spearman") model.dados40 <- specify.model() F1 -> Item11, lam11, NA F1 -> Item31, lam31, NA F1 -> Item36, lam36, NA F1 -> Item54, lam54, NA F1 -> Item63, lam63, NA F1 -> Item65, lam55, NA F1 -> Item67, lam67, NA F1 ->