similar to: About the efficiency of R optimization function

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:

>>>>> Duncan Murdoch >>>>> on Sun, 26 Mar 2023 12:41:03 -0400 writes: > On 26/03/2023 11:54 a.m., J C Nash wrote: >> A tangential email discussion with Simon U. has >> highlighted a long-standing matter that some tools in the >> base R distribution are outdated, but that so many >> examples and other tools may use

Hi, We (Paul Gilbert and I) have just released a new R package on CRAN called "BB" (stands for Barzilai-Borwein) that provides functionality for solving large-scale (and small-scale) nonlinear system of equations. Until now, R didn't have any functionality for solving nonlinear systems. We hope that this package fills that need. We also have an implementation of the

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

Dear R-help list, I am working on an optimization with R by evaluating a likelihood function that contains lots of Gamma calculations (BGNBD: Hardie Fader Lee 2005 Management Science). Since I am forced to implement lower bounds for the four parameters included in the model, I chose the optim() function mith L-BFGS-B as method. But the likelihood often returns inf-values which L-BFGS-B

Hello everyone! When I use "nlminb" to minimize a function with a variable of almost 200,000 dimension, I got the following error. > nlminb(start=start0, msLE2, control = list(x.tol = .001)) Error in vector("double", length) : vector size specified is too large I had the following setting options(expressions=60000) options(object.size=10^15) I have no idea about what

Hello all, I have a large parameter problem with the following very simple likelihood function: fn<-function(param) { x1<-param[1:n] g1<-param[(n+1):(2*n)] beta<-param[(2*n+1):(2*n+k)] sigma2<-param[2*n+k+1]^2 meang1sp<-mean(g1[sp]) mu<-beta%*%matrix(x1,1,n)-(g1[sp]-meang1sp)%*%matrix(g1,1,n) return(sum((ydc-mu)^2)/(2*sigma2) + n*k*log(sqrt(sigma2)) +

Don't know if this was corrected in 2.3.4 (haven't upgraded yet but didn't see it in the notes) - but in 2.3.3 I see this in my log: imap-login: Error: Diffie-Hellman key exchange requested, but no DH parameters provided. Set ssh_dh=</path/to/dh.pem So...either there's an undocumented feature of SSH-over-IMAP (that's Dovecot - always on the cutting edge!) or someone had

Debian sid package v. 2.6.4-2.3 UPS nitram elite 2002 700VA (serial port) MOBO A7V8X-X ================================ Hi list, Everything work fine, except after an AC supply shortage: the UPS don't come back to a normal behavior, it stays on battery (of course, it works right w/o any cable). Is there something I can do recover a normal behavior? JY -- Too much of a good thing is

Recently I updated to Hardy Heron(Ubuntu beta) and with it cam openssh-client 4.7p1. In my environment we have alot of Extreme(www.extremenetworks.com) switch devices which we access via ssh. 4.7p1 would no longer allow me to connect to the switches, however 4.6p1 would. The error I received was. ' channel 0: open failed: resource shortage: Channel open failed' I did some diggin and

I'm currently using the Linksys PAP2, and since there's a shortage I'm looking for different devices. I'm mainly looking at the Sipura SPA sets since they are the base of the pap2. Anyone else have experience using them, and which one? Thanks Sherwood McGowan -------------- next part -------------- An HTML attachment was scrubbed... URL:

Hi, All: Is there a simple way to detect complex conjugates in the roots returned by 'polyroot'? The obvious comparison of each root with the complex conjugate of the next sometimes produces roundoff error, and I don't know how to bound its magnitude: (tst <- polyroot(c(1, -.6, .4))) tst[-1]-Conj(tst[-2]) [1] 3.108624e-15+2.22045e-16i

My log is showing errors like May 1 05:14:17 corn kernel: [6822807.017625] EXT3-fs warning (device dm-7): ext3_dx_add_entry: Directory index full! Judging from the minor device numbers in /dev/mapper, that corresponds to my mail spool. My searches suggest that the problem indicates an individual directory has too many files in it. There does not seem to be a general shortage of inodes or space.

Hi All, I'm a Speex newbie wanting to figure if it's worth trying to get the fixed point decoder working on an M32C processor. It has a hardware 16x16->32 multiply and a 16x16+48->48 multiply/accumulate in about 8 cycles and runs at 25Mhz. No shortage of RAM. I'm confident that I could make it work and am willing to commit the effort, but before I do so I should ask: 1) Does

While doing pls I found the following problem > BHPLS1 <- plsr(GroupingList ~ PCIList, ncomp = 10, data = PLSdata, jackknife = >FALSE, validation = "LOO") when not enabling jackknife the command works fine, but when trying to enable jackknife i get the following error. >BHPLS1 <- plsr(GroupingList ~ PCIList, ncomp = 10, data = PLSdata, jackknife = >TRUE,

Hi, list, I'm going to deploy postfix + dovecot + CephFS( as Mail Storage). Basically I want to use two servers for them, which is kind of HA. My idea is that using keepalived or Pacemaker to host a VIP, which could fail over the other server once one is down. And I'll use Haproxy or Nginx to schedule connections to one of those server based on source IP( Session stickiness),

Hi Does anyone know of any R coding/functions for MCMC approaches? I am currently using BUGS but I wonder if the bazaar has produced anything? I think I am pushing BUGS to it's limit and possibly past it at the moment. John -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html Send

Is there a function in R that returns the complex conjugate of a matrix (a la 'CONJ' in IDL or 'Conjugate' in Mathmatica)?

Hi, I am have a data set of around 43000 probes(rows), and have to calculate correlation matrix. When I run cor function in R, its throwing an error message of RAM shortage which was obvious for such huge number of rows. I am not getting a logical way to cut off this huge number of entities, is there an alternative to pearson correlation or with other dist() methods calculation(euclidean) that

Hi all, I've been working on improving R's optim() command, which does general purpose unconstrained optimization. Obviously, this is important for many statistics computations, such as maximum likelihood, method of moments, etc. I have focused my efforts of the BFGS method, mainly because it best matches my current projects. Here's a quick summary of what I've done: *