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...el with the present day version of R so that R can now be directly compared with AD Model Builder for this type of model. I have put the results of the test together with the original Schnute and Richards paper and the working R and AD Model Builder codes on Otter's web site http://otter-rsch.ca/tresults.htm The results are that AD Model builder is roughly 1000 times faster than 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 o...

Dear R-users, Half a year ago we put out the R package "glmmADMB" for fitting overdispersed count data. http://otter-rsch.com/admbre/examples/glmmadmb/glmmADMB.html Several people who used this package have requested additional features. We now have a new version ready. The major new feature is that glmmADMB allows Bernoulli responses with logistic and probit links. In addition there is a "ranef.glmm.admb()&quot...

I'm attempting to calculate a regression in R that I normally use Prism for, because the formula isn't pretty by any means. Prism presents the formula (which is in the Prism equation library as Heterologous competition with depletion, if anyone is curious) in these segments: KdCPM = KdnM*SpAct*Vol*1000 R=NS+1 S=(1+10^(X-LogKi))*KdCPM+Hot a=-1*R b=R*S+NS*Hot+BMax c = -1*Hot*(S*MS+BMax) Y

...Linux. I believe those people must feel quite confident that they are not covered (or "infected"?) by GPL. Just my $0.02... Andy _____ From: r-help-bounces at stat.math.ethz.ch on behalf of Spencer Graves Sent: Fri 5/19/2006 6:43 PM To: mschwartz at mn.rr.com Cc: otter at otter-rsch.com; r-help at stat.math.ethz.ch; Damien Joly Subject: Re: [R] How can you buy R? [Broadcast] I'd like to know what people think is the meaning of section 2.b of the GPL (http://www.gnu.org/copyleft/gpl.html#SEC1): "You must cause any work that you distribute or p...

...ely available R package glmmADMB can do Adaptive Gaussian Quadrature for this type of model, since it is built using AD Model 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

...you know of a free R package, glmm.ADMB, that can handle mixed models for overdispersed and zero-inflated count data (negativebinomial and poisson). It was built using AD Model Builder software (Otter Research) for random effects modeling and is available (for free and runs in R) at: http://otter-rsch.com/admbre/examples/glmmadmb/glmmADMB.html I have been using this package for a split plot design along streams (my M.Sc thesis). My response data was best described by a negative binomial distribution (without zero-inflation) (beaver dam counts). The model worked very well for my dataset and a...

> 1. A problem between smbclient and a share with windows 3.11 (victor3.lopes@voila.fr) > 2. RE: A problem between smbclient and a share with windows 3.11 (Allen, Michael B (RSCH)) > > --__--__-- > > Message: 1 > Date: Fri, 23 Feb 2001 13:03:34 +0100 > Subject: A problem between smbclient and a share with windows 3.11 > From: "victor3.lopes@voila.fr" <victor3.lopes@voila.fr> > To: "Mailing list samba" <smb-clients@list...

Hi I am running an lmer which works fine with family=poisson mixed.model<-lmer(nobees~spray+dist+flwabund+flwdiv+round+(1|field),family="poisson",method="ML",na.action=na.omit) But it is overdispersed. I tried using family=quasipoisson but get no P values. This didnt worry me too much as i think my data is closer to negative binomial but i cant find any examples of

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

...seconds or less (although the more complicated turns out to be overparameterized) Using the random effects module of AD Model Builder we have developed a shared library (Windows dll) that can be called from R via the driver function glmm.admb(). The function can be downloaded from http://otter-rsch.com/admbre/examples/nbmm/nbmm.html The two models of Booth et al are fit by the commands: glmm.admb(y~Base*trt+Age+Visit,random=~1,group="subject",data=epil2) glmm.admb(y~Base*trt+Age+Visit,random=~Visit,group="subject",data=epil2) I will be happy to receive feedback on the f...

...values for the log-likelihood with the different packages and methods. We thought it would be interesting to revisit this example using the AD Model Builder random effects module which we feel is the most stable software available for this problem at this time. http://otter-rsch.com/admodel.htm You can get Table 2 from Lesaffre et al at http://otter-rsch.com/downloads/other/lesaffre.pdf The data and more information are available from the publisher. http://www.blackwellpublishers.co.uk/rss/Volumes/Cv50p3.htm We considered three questi...

...ns for nonlinear robust regression, > > analogous to e.g. LTS? > > > > Searching google I have found > > 1, an abstract to generalize LTS for nonlinear regression > > models, see: http://smealsearch.psu.edu/1509.html > > 2, an AD-model builder, see: http://otter-rsch.com/admodel/cc1.html > > but no mention of R/S > > > > Thank you in advance > > Best regards > > Christian > > _._._._._._._._._._._._._._._._ > > C.h.i.s.t.i.a.n S.t.r.a.t.o.w.a > > V.i.e.n.n.a A.u.s.t.r.i.a > > _._._._._._._._._._._._._...

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,

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 |

...ce functions, such as predict(), fitted.values(), ... are still missing from this package, but will hopefully be added in later versions (contributions/suggestions are most welcome). Other response distributions than negative binomial or Poisson could easily be added. Download site: http://otter-rsch.com/admbre/examples/glmmadmb/glmmADMB.html The package is based on the software ADMB-RE, but the full unrestricted R-package is made freely available by Otter Research Ltd and does not require ADMB-RE to run with user supplied data. I you will find this useful, Hans Skaug -- Hans Skaug Depar...

Does someone have code, or point to a source to get it, to model repeated measures zero-inflated poisson data. The data come from a replicated field trial comparing two treatments - a control and a test treatment. Thanks in advance ------------------------------------ Subhash Chandra, DSc Senior Biometrician Primary Industries Research Victoria Department of Primary Industries 1 Ferguson Road

...html http://finzi.psych.upenn.edu/R/Rhelp02a/archive/48646.html *this refers to the random effects module of AD Model Builderthat can be called from R via the driver functon glmm.admb(). Their example problem fits the model with a negative binomial. The function can be downloaded from http://otter-rsch.com/admbre/examples/nbmm/nbmm.html ************ *********** My Original Query Greetings R Users! I have a data set of count responses for which I have made repeated observations on the experimental units (stream reaches) over two air photo dates, hence the mixed effect. I have been using Dr. Ji...

...ally 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