similar to: Automatic differentiation (was: Re: D(dnorm...)?)

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

Dear Dr Skaug and R users, just discovered glmm.admb in R, and it seems a very useful tool. However, I ran into a problem when I compare two models: m1<-glmm.admb(survival~light*species*damage, random=~1, group="table", data=bm, family="binomial", link="logit") m1.1<-glmm.admb(survival~(light+species+damage)^2, random=~1, group="table", data=bm,

In efforts to improve optimization tools for R, one of my interests has been getting automatic differentiation capabilities so that analytic rather than numerical derivatives can be used. They would be helpful in several other areas besides optimization, My timings show factors of the order of 1000s in time improvements by avoiding numerical derivatives in some cases. There has been some work in

Hi I recently gave a presentation about Automatic Differentiation (AD) and R at the Eighth Euro AD Workshop in Oxford (17/07/09). The presentation was intended as a general introduction to R and the desire for a generic AD interface for R. During the presentation I emphasised the need and the high level of interest that the R community has in developing such an interface and that input from the

Can someone help me understand the following: > D(expression(dnorm(x, mean)), "mean") [1] 0 > sessionInfo() R version 2.2.1, 2005-12-20, i386-pc-mingw32 attached base packages: [1] "methods" "stats" "graphics" "grDevices" "utils" "datasets" [7] "base" By my computations, this should be

Dear R-users, A recent post (Feb 16) to R-help inquired about fitting a glmm with a negative binomial distribution. Professor Ripley responded that this was a difficult problem with the simpler Poisson model already being a difficult case: https://stat.ethz.ch/pipermail/r-help/2005-February/064708.html Since we are developing software for fitting general nonlinear random effects models we

Do Users of Nonlinear Mixed Effects Models Know Whether Their Software Really Works? Lesaffre et. al. (Appl. Statist. (2001) 50, Part3, pp 325-335) analyzed some simple clinical trials data using a logistic random effects model. Several packages and methods MIXOR, SAS NLMIXED were employed. They reported obtaining very different parameter estimates and P

Dear R-users, Earlier this year I posted a message to this list regarding negative binomial mixed models in R. It was suggested that the program I had written should be turned into an R-package. This has now been done, in collaboration with David Fournier and Anders Nielsen. The R-package glmmADMB provides the following GLMM framework: - Negative binomial or Poisson responses. - Zero-inflation

Dear List, Some of you have been following the discussion of the GPL and its inclusion in the glmmADMB package we created for R users. I would like to provide a bit of background and include an email we received from Prof. Ripley so that everyone can be aware of how some might use the GPL to try to force access to proprietary software. I think this is interesting because many have voiced the

7 Jan 09 Hello, I am using R version 2.7.0 in a Windows XP context. I am also using the glmm.admb package (created by Dave Fournier, Hans Skaug, and Anders Nielson) to run mixed-effects negative binomial models. To the best of my knowledge and ability, I have searched and studied the R-help, R-sig-mixed models, and ADMB NBMM for R (through Otter Research Ltd) list servs; R help

For those of you who want to learn how to integrate AD Model Builder with R, and are going to the JSM in Seattle, the following course may be of interest: Statistical and ecological modeling in AD Model Builder Date: August 5, 2006 (the day before the Joint Statistical Meetings open) For more information see: http://www.mi.uib.no/~skaug/admb/seattleworkshop.html Regards, hans

the code is list below , i can run this code for laplace approximation but not importance sampling. the code work properly if use impSamp=0 , but error for any other number >0 . could you guys help me out. thanks so much ! source("http://www.mi.uib.no/~skaug/cash/lesaffre_dat.s") library(glmmADMB) fit_glmmADMB_ip <-

Hi here, i recently notice the software built by otter company know as AD-MB tools . i explore a little bit this tools under the R Package for mixed logistics model. it is a very interesting tool. but i get several questions. first question: i tried the R code below, and have the error , i can run the code for switching the setting to impSamp=0 , it means i can only run the code under

There has recently been some discussion on the list about AD Model builder and the suitability of R for constructing the types of models used in fisheries management. https://stat.ethz.ch/pipermail/r-help/2006-January/086841.html https://stat.ethz.ch/pipermail/r-help/2006-January/086858.html I think that many R users understimate the numerical challenges that some of the typical

Martin (see below) gives a good explanation of the difference between AD and symbolic differentiations. I'm of the opinion we can use both. However, the real issue as far as I'm concerned (from an optimizer's point of view, which may also be that of ODE and PDE folk) is that right now none of the offerings that we have are easy to use. Indeed, usability is one of the key issues in my

Dear all, I am the author of an open-source package for mathematical optimization and automatic differentiation called CasADi (www.casadi.org) and have recently started realize the potential of the LLVM project. At the core of CasADi are two fast interpretors for mathematical expressions and I'm now planning to complement these with JIT-compilation using LLVM. Does anyone know if there is

Dear all, I'm wondering if there are some ongoing projects for interior point methods in R (e.g. linking ipopt from Coin written in C++ to R) and for automatic differentiation in R (e.g. linking openAD available in C++ and Fortran) ? Many thanks, David [[alternative HTML version deleted]]

Hi R People: Is there a package for automatic differentiation, please? thanks in advance, Erin -- Erin Hodgess Associate Professor Department of Computer and Mathematical Sciences University of Houston - Downtown mailto: erinm.hodgess at gmail.com

Hi, no-one else has said anything more pertinent so here's my two-pence. I have been thinking for a while about LLVM in the context of simulating _small_ stochastic systems by which I mean very much non-trivial stochastic transition functions, but still small enough that if compiled carefully down to machine code via LLVM with a good chance that they'll be faster. (With even

Greetings, My team at Numerix LLC (www.numerix.com) is spinning up what I expect to be a long term effort using LLVM to generate fast code for calculations on financial instruments. One area we will apply apply LLVM is compiling instead of interpreting our domain specific language (DSL) that our customers use for modeling complex financial instruments to dramatically improve performance. A less