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...n R for this problem. ADMB takes about 2 seconds to converge while R takes over 90 minutes. This is a simple toy example. Real fisheries models are often hundred of times more computationally intensive as this one. Cheers, Dave ~ -- David A. Fournier P.O. Box 2040, Sidney, B.C. V8l 3S3 Canada Phone/FAX 250-655-3364 http://otter-rsch.com

...del Builder's random effects module which incorporates this feature. There is now a beta version of the software for people using R on the Mac intel platform. http://otter-rsch.com/admbre/examples/glmmadmb/glmmADMB.html Cheers, Dave -- David A. Fournier P.O. Box 2040, Sidney, B.C. V8l 3S3 Canada Phone/FAX 250-655-3364 http://otter-rsch.com

.../ Two areas where AD Model builder would be especially useful to R users are multi-parmater smooth optimization as in larg scale maximum likelihood estimation and the analysis of general nonlinear random effects models. Cheers, Dave -- David A. Fournier P.O. Box 2040, Sidney, B.C. V8l 3S3 Canada Phone/FAX 250-655-3364 http://otter-rsch.com

Has there been any follow up to this question? I have found myself wondering the same thing: How then does SAS fit a beta distributed GLMM? It also fits the negative binomial distribution. Both of these would be useful in glmer/lmer if they aren't 'illegal' as Brian suggested. Especially as SAS indicates a favorable delta BIC of over 1000 when I fit the beta to my data (could be the

One of my colleagues has a data set from a two-level nested design from which we would like to estimate variance components. But we'd like some idea of what the inevitable outliers are doing, so we were looking for something in R that uses robust (eg Huber) treatment and returns robust estimates of variance. Nothing in my collection of R robust estimation packages (robust, robustbase and MASS

...ompiler on windows or probably easier on Linux i686. I would appreciate any advice on how how to go about this. I understand there are a number of different versions of Mac OS X. Are there compatability issues? also 32/64 bit issues. Dave -- David A. Fournier P.O. Box 2040, Sidney, B.C. V8l 3s3 Canada http://otter-rsch.com --

Dear R People: When looking at the previous postings regarding TRAMO-SEATS, I am somewhat puzzled. Is it true that we CANNOT replicate TRAMO-SEATS because of licensing or ownership issues, please? If not, would anyone be interested in an R version of it, please? Thanks, Sincerely, Erin Hodgess Associate Professor Department of Computer and Mathematical Sciences University of Houston -

R-help, I'm trying to estimate some parameters using the Maximum Likehood method. The model describes fish growth using a sigmoidal-type of curve: fn_w <- function(params) { Winf <- params[1] k <- params[2] t0 <- params[3] b <- params[4] sigma <- params[5] what <- Winf * (1-exp(- k *(tt - t0)))^b

Hello, I'm running a simulation study of a multilevel model with binary response using the binomial probit link. It is a random intercept and random slope model. GLMMPQL and lmer fail to converge on a *significant* portion of the *generated* datasets, while MlWin gives reasonable estimates on those datasets. This is unacceptable. Does anyone has similar experiences? Regards, Roel de

...then yes we would need unwinding > information. We'd also need unwinding information in libunwind if it > called a function that could throw an exception. > >> I tried the >> example with the armv7l release of clang 8.0 which I happened to have >> installed on an Armv8l machine and the program worked. I was able to >> reproduce the problem with the PR with the default Ubuntu16.04 clang >> (3.8) and libc++-dev package. >> >> I also note that when looking at the link line for the example in the >> PR, clang was linking libgcc_s and not...

...nberger at pgc.nrcan.gc.ca or andreas at arescon.com -- ___________________________________________________________________ a. rosenberger arescon ltd. andreas at arescon.com 9706 First St. www.arescon.com Sidney, B.C. Canada V8L 3C7 ___________________________________________________________________

...extend methods based one the Laplace approximation for the random effects (i.e. the Laplace approximation itself, adaptive Gaussian integration, adaptive importance sampling) to the new distribution. Dave -- David A. Fournier P.O. Box 2040, Sidney, B.C. V8l 3S3 Canada Phone/FAX 250-655-3364 http://otter-rsch.com

Dear useRs (called Frank Harrell, most likely), after having preached for years to my medical colleagues to be cautious with stepwise selection procedures, they chanted back asking for an alternative when using mixed models. There is a half dozen laXXX packages around for all types of linear models, but as far I see there is none for mixed models such as lme. Even boot.stepAIC (which I

...lem if an > exception were being propagated through a libunwind function, and that > shouldn't happen unless something has gone badly wrong. Can you explain what you mean? > I tried the > example with the armv7l release of clang 8.0 which I happened to have > installed on an Armv8l machine and the program worked. I was able to > reproduce the problem with the PR with the default Ubuntu16.04 clang > (3.8) and libc++-dev package. > > I also note that when looking at the link line for the example in the > PR, clang was linking libgcc_s and not libunwind so I thin...

...would need unwinding >> information. We'd also need unwinding information in libunwind if it >> called a function that could throw an exception. >> >> I tried the >> example with the armv7l release of clang 8.0 which I happened to have >> installed on an Armv8l machine and the program worked. I was able to >> reproduce the problem with the PR with the default Ubuntu16.04 clang >> (3.8) and libc++-dev package. >> >> I also note that when looking at the link line for the example in the >> PR, clang was linking libgcc_s and not...

Hello, I am using odesolve to simulate a group of people moving through time and transmitting infections to one another. In Matlab, there is a NonNegative option which tells the Matlab solver to keep the vector elements of the ODE solution non-negative at all times. What is the right way to do this in R? Thanks, Jeremy P.S., Below is a simplified version of the code I use to try to do this,

Hello, I am running R 2.6.1 on windows xp I am trying to fit a cox proportional hazard model with a shared Gaussian frailty term using coxme My model is specified as: nofit1<-coxme(Surv(Age,cen1new)~ Sex+bo2+bo3,random=~1|isl,data=mydat) With x1-x3 being dummy variables, and isl being the community level variable with 4 levels. Does anyone know if there is a way to get the standard error

I am using the 'glmmPQL function in the 'MASS' library to fit a mixed effects logistic regression model to simulated data. I am conducting a series of simulations, and with certain simulated datasets, estimation of the random effects logistic regression model unexpectedly terminates. I receive the following error message from R: Error in lme.formula(fixed=zz + arm.long,random=~1 |

...s out there. We would welcome results for other packages. If we can find a serious competitor to AD Model Builder then we could move on to comparing the relative performance on more difficult models. Cheers, Dave Fournier -- David A. Fournier P.O. Box 2040, Sidney, B.C. V8l 3s3 Canada http://otter-rsch.com -- Internal Virus Database is out-of-date.

I'd like to fit linear models on very large datasets. My data frames are about 2000000 rows x 200 columns of doubles and I am using an 64 bit build of R. I've googled about this extensively and went over the "R Data Import/Export" guide. My primary issue is although my data represented in ascii form is 4Gb in size (therefore much smaller considered in binary), R consumes about