similar to: another optimization question

GENERAL REFERENCE ON NONLINEAR OPTIMIZATION? What are your favorite references on nonlinear optimization? I like Bates and Watts (1988) Nonlinear Regression Analysis and Its Applications (Wiley), especially for its key insights regarding parameter effects vs. intrinsic curvature. Before I spent time and money on several of the refences cited on the help pages for "optim",

Hi everyone. I have a problem that I have been unable to determine either the best way to proceed and why the methods I'm trying to use sometimes fail. I'm using the pf() function in an optimization function to find a noncentrality parameter that leads to a specific value at a specified quantile. My goal is to have a general function that returns the noncentrality parameter that

I'm a very recent user of R. I have been adapting my Splus programmes and I found only one (important) problem. There exists no function "nlmin" in R and its substitute, "nlm", does not work well with my kind of problems, sometimes no achieving convergence, other tines "converging" to impossible values. My models are highly nonlinear and are to be estimated by

Dear all, I have found a bug in nlm() and would like to submit a report on this. Since nlm() is in the stats-package, which is maintained by the R Core team, bug reports should be submitted to R's Bugzilla. However, I'm not a member of Bugzilla. Could anyone be so kind to add me to R's Bugzilla members or let me know to whom I should send the bug report? Thank you in advance. Kind

This message is in MIME format. The first part should be readable text, while the remaining parts are likely unreadable without MIME-aware tools. --1660387551-1458482416-1249639718=:2997 Content-Type: TEXT/PLAIN; CHARSET=US-ASCII; FORMAT=flowed Content-ID: <Pine.LNX.4.64.0908071039211.2997 at parser.ilovebacon.org> Hello, There appears to be a bug in the nlm function, which I

It would be really nice if nlm took a set of "..." optional arguments that were passed through to the objective function. This level of hacking is probably slightly beyond me: is there a reason it would be technically difficult/inefficient? (I have a vague memory that it used to work this way either in S-PLUS or in some previous version of R, but I could easily be wrong.) Here's

Dear expeRts, first of all I'd like to thank you for the quick help on my last which() problem. Here is another one I could not tackle: I have data on an absorption measurement which I want to fit with an voigt profile: fn.1 <- function(p){ for (i1 in ilong){ ff <- f[i1] ex[i1] <- exp(S*n*L*voigt(u,v,ff,p[1],p[2],p[3])[[1]]) } sum((t-ex)^2) } out <-

Hi R-help! I'm trying to understand how R's nlm function updates its estimate of the Hessian matrix. The Dennis/Schnabel book cited in the references presents a number of different ways to do this, and seems to conclude that the positive-definite secant method (BFGS) works best in practice (p201). However, when I run my code through the optim function with the method as "BFGS",

I've been working on a new package and I have a few questions regarding the behaviour of the nlm function. I've been (for better or worse) using the nlm function to fit a linear model without suppling the hessian or gradient attributes in the objective function. I'm curious as to why the nlm requires 31 iterations (for the linear model), and then it doesn't work when I try to add

In the course of revising a paper I have had occasion to attempt to maximize a rather complicated log likelihood using the function nlm(). This is at the demand of a referee who claims that this will work better than my proposed use of a home- grown implementation of the Levenberg-Marquardt algorithm. I have run into serious hiccups in attempting to apply nlm(). If I provide gradient and

This message is in MIME format. The first part should be readable text, while the remaining parts are likely unreadable without MIME-aware tools. --1660387551-150661043-1249684349=:2997 Content-Type: TEXT/PLAIN; charset=iso-8859-1; format=flowed Content-Transfer-Encoding: QUOTED-PRINTABLE Hi Jeff, =09As mentioned in my message, I *did* replicate on another platform.=20 One platform was

Hello everyone! I am having some trouble supplying the gradient function to nlm in R for windows version 2.2.1. What follows are the R-code I use: fredcs39<-function(a1,b1,b2,x){return(a1+exp(b1+b2*x))} loglikcs39<-function(theta,len){ value<-sum(mcs39[1:len]*fredcs39(theta[1],theta[2],theta[3],c(8:(7+len))) - pcs39[1:len] * log(fredcs39(theta[1],theta[2],theta[3],c(8:(7+len)))))

Dear list, I am using optim() function to MLE ~55 parameters, but it is very slow to converge (~ 25 min), whereas I can do the same in ~1 sec. using ADMB, and ~10 sec using MS EXCEL Solver. Are there any tricks to speed up? Are there better optimization functions? Thanks Toshihide "Hamachan" Hamazaki, $B_@:j=S=((JPhD Alaska Department of Fish and Game:

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Dear useRs, I have just discovered that the R optim function does not return the number of iterations. I still wonder why line 632-634 of optim C, the iter variable is not returned (for the BFGS method for example) ? Is there any trick to compute the iteration number with function call number? Kind regards Christophe -- Christophe Dutang Ph.D. student at ISFA, Lyon, France website:

Hi, I'm trying to fit some data using a logistic function defined as y ~ a * (1+m*exp(-x/tau)) / (1+n*exp(-x/tau) My data is below: x <- 1:100 y <- c(0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0, 0,0,0,0,0,1,1,1,2,2,2,2,2,3,4,4,4,5, 5,5,5,6,6,6,6,6,8,8,9,9,10,13,14,16,19,21, 24,28,33,40,42,44,50,54,69,70,93,96,110,127,127,141,157,169,

Dear R-users, I am trying to find the MLEs for a loglikelihood function (loglikcs39) and tried using both optim and nlm. fredcs39<-function(b1,b2,x){return(exp(b1+b2*x))} loglikcs39<-function(theta,len){ sum(mcs39[1:len]*fredcs39(theta[1],theta[2],c(8:(7+len))) - pcs39[1:len] * log(fredcs39(theta[1],theta[2],c(8:(7+len))))) } theta.start<-c(0.1,0.1) 1. The output from using optim is

Hello. I am getting results from sem that are not correct (that's assuming that the results from my AMOS 4.0 software are correct). sem does not vary some of the parameters substantially from their starting values, and the final estimates of those parameters as well as the model chisquare value are incorrect. I've attached some code that replicates the problem. The parameters in

Hello, I'm not sure this is doable but I'm having trouble running my R script with multithreaded capability. With 16x2.93Ghz CPUs available, only one is running with 100%. Any suggestions? Thanks, Bing My system configuration is: egenera virtual machine running Linux Red Hat Enterprise Linux Server release 5.1 (Tikanga) 16x2.93GHz CUPs 99G memory

Hello: Below is a toy logistic regression problem. When I wrote my own code, Newton-Raphson converged in three iterations using both the gradient and the Hessian and the starting values given below. But I can't get nlm() to work! I would much appreciate any help. > x [1] 10.2 7.7 5.1 3.8 2.6 > y [1] 9 8 3 2 1 > n [1] 10 9 6 8 10 derfs4=function(b,x,y,n) {