similar to: optim with gradient

°_§É§¿§¿ ----- Original Message ----- From: <r-help-request at stat.math.ethz.ch> To: <r-help at stat.math.ethz.ch> Sent: Sunday, December 08, 2002 7:00 PM Subject: R-help digest, Vol 1 #10 - 6 msgs > Send R-help mailing list submissions to > r-help at stat.math.ethz.ch > > To subscribe or unsubscribe via the World Wide Web, visit >

I use optim to compute maximum likelihood estimations without giving an analytical gradient to optim. However, I would like to get an output of the final numerical gradient vector and the final matrix of contributions to the gradient. But I did not find any mention of this kind of output in help pages. Does anyone know how to do that ? Stephane Luchini GREQAM Marseille, France

It is much more efficient to calculate the value of the log-likelihood and it's gradient at the same time rather than calculating both by separate functions. Is there a way to use optim so that there is one call to a function that calculates both. -- View this message in context:

I am calling 'vmmin' several times from a C function (which is called via .C). It works very well, except for memory consumption. The cause is that vmmin allocates memory via R_alloc, and this memory is not freed as vmmin exits. Instead all the allocated memory is freed on return of the .C call. In one application, I have 2000 functions of 500 variables each to minimize. In each call to

Dear R users When I use OPTIMX with BFGS, I've got the following error message. ----------------------------------------------------------------- > optimx(par=theta0, fn=obj.fy, gr=gr.fy, method="BFGS") Error: Gradient function might be wrong - check it! ----------------------------------------------------------------- So, I checked and checked my gradient function line by

Hi all, I would like to use optim() to estimate the equation by the log-likelihood function and gradient function which I had written. I try to use OPG(Out Product of Gradient) to calculate the Hessian matrix since sometime Hessian matrix is difficult to calculate. Thus I want to pick the Gradient matrix from the gradient function. Moreover, could R show the process of calculation on gradient

I noticed the same thing as I reported below, when I upgraded from R-2.0.0-alpha-20040918 to today's beta version: 'R CMD check' failed as before; but after cleaning 'src' from .o and .so files, it worked again. So the two-day-old '.so' file is obviously different from today's. Has compiler directives changed in the two last days? Or what is happening? G?ran On

Hi, I'm very interested in using the constrOptim() function currently in the R-devel sources. In particular, I'm trying to fit point process conditional intensity models via maximum likelihood. However, I noticed that the gradient of the objective function must be supplied for all but the Nelder-Mead method. I was wondering why this was because optim() itself does not require a gradient

Hi, i''m trying to use a visual indicator for my Ajax requests. It''s based on the shopping cart demo at script.aculo.us and works great in Firefox, Konqueror and Opera, but fails in IE6. For some reason (timing problems?) onComplete is executed before onLoading, so the indicator is shown but not hidden when the request has finished. Oddly enough it works fine in the shopping

Dear all, I am using the functions 'optim' and 'nlminb'. For both, you can provide a function which computes the gradient of the objective function (to enhance speed and precision). In my case, both the objective function and the gradient take time to be computed and share many common computations (similar matrix, products, etc...). Therefore, I have to compute these

Dear R users When I use OPTIM with BFGS, I've got a significant result without an error message. However, when I use OPTIMX with BFGS( or spg), I've got the following an error message. ---------------------------------------------------------------------------------------------------- > optimx(par=theta0, fn=obj.fy, gr=gr.fy, method="BFGS", >

Dear R help, I am trying solve an MLE convergence problem: I would like to estimate four parameters, p1, p2, mu1, mu2, which relate to the probabilities, P1, P2, P3, of a multinomial (trinomial) distribution. I am using the mle2() function and feeding it a time series dataset composed of four columns: time point, number of successes in category 1, number of successes in category 2, and

Dear Rhelpers I have the problem with initial values, could you please tell me how to solve it? Thank you June > p = summary(maxLik(fr,start=c(0,0,0,1,0,-25,-0.2))) Error in maxRoutine(fn = logLik, grad = grad, hess = hess, start = start, : NA in the initial gradient > p = summary(maxLik(fr,start=c(0,0,0,1,0,-25,-0.2),method="BFGS")) Error in optim(start, func, gr =

Dear R-help subscribers; I have a question regarding making gradients in R. I've searched on the web, but was only able to find functions that make a gradient between color X and Y, which is not what I want. I want to 'pick out' individual, smaller pieces of a gradient based on a range of numbers. Say that I have a range of numbers, leading from 0 to 1. Then I want 0 to refer to

<FONT face="Default Sans Serif, Verdana, Arial, Helvetica, sans-serif" size=2><DIV>Dear list members,</DIV><DIV>&nbsp;</DIV><DIV>I am trying to use "nlm" function to maximize a mixture likelihood of beta densities. There are five unknown parameters in the likelihood. Since I can get the analytic gradient, I attach the "gradient"

Dear friends. I use nls() and encounter the following puzzling problem: I have a function f(a,b,c,x), I have a data vector of x and a vectory y of realized value of f. Case1 I tried to estimate c with (a=0.3, b=0.5) fixed: nls(y~f(a,b,c,x), control=list(maxiter = 100000, minFactor=0.5 ^2048),start=list(c=0.5)). The error message is: "number of iterations exceeded maximum of

Hi everyone, I am currently using the function optim() to maximize/minimize functions and I would like to see more output of the optimization procedure, in particular the numerical gradient of the parameter vector during each iteration. The documentation of optim() describes that the trace parameter should allow one to trace the progress of the optimization. I use the following command:

Hello No worries anymore. Figured it out. Thanks for everything. Luz ---------- Forwarded message ---------- Date: Sun, 18 Jun 2006 23:12:25 -0600 (MDT) From: Luz Maria Palacios Derflingher <palacios at math.ucalgary.ca> To: r-help at lists.R-project.org Cc: r-help at stat.math.ethz.ch. Subject: help on nlm (gradient) Hello. I am having some trouble using nlm in R for windows version

Content-Type: text/plain; charset="iso-8859-1" Content-Transfer-Encoding: 7bit X-Virus-Scanned: by amavisd-new X-Spam-Checker-Version: SpamAssassin 2.63 (2004-01-11) on hypatia.math.ethz.ch X-Spam-Level: **** X-Spam-Status: No, hits=4.2 required=5.0 tests=MSGID_FROM_MTA_HEADER,RCVD_IN_BL_SPAMCOP_NET autolearn=no version=2.63 Dear r-help list, my question is about ordination technics:

G=F6ran, At 11:04 07/12/01 +0100, G=F6ran Brostr=F6m wrote: >On Wed, 5 Dec 2001, G=F6ran Brostr=F6m wrote: > >[...] >=20 >> My real problem is how to create a data frame in a sequentially growing >> manner, when I know the final size (no of cases). I want to avoid to >> call 'rbind' many times, and instead create an 'empty' data frame in >> one