search for: ucminf

Hey, R Users my windows is 64 bit windows 7.?I am trying to install the package ucminf into my 64 bit version R but cannot.??the package I downloaded is from http://cran.r-project.org/web/packages/ucminf/index.html?and I installed it with the "install from local zip files", due to I did not connect my computer to internet. did anyone meet this problem and is there a...

...moothed noise functions we get for instance the following results: (Starting point is always `rep(0.1, 5)`, maximal number of iterations 5000, relative tolerance 1e-12, and the optimization is successful if the function value at the minimum is below 1e-06.) k nmk anms neldermead ucminf optim_BFGS --------------------------------------------------- 1 0.21 0.32 0.13 0.00 0.00 3 0.52 0.63 0.50 0.00 0.00 10 0.81 0.91 0.87 0.00 0.00 Solvers: nmk = dfoptim::nmk, anms = pracma::anms [both N...

Ravi Varadhan and I have been looking at UCMINF to try to identify why it gives occasional (but not reproducible) errors, seemingly on Windows only. There is some suspicion that its use of DBLEPR for finessing the Fortran WRITE() statements may be to blame. While I can find DBLEPR in Venables and Ripley, it doesn't get much mention after abo...

Ravi Varadhan and I have been looking at UCMINF to try to identify why it gives occasional (but not reproducible) errors, seemingly on Windows only. There is some suspicion that its use of DBLEPR for finessing the Fortran WRITE() statements may be to blame. While I can find DBLEPR in Venables and Ripley, it doesn't get much mention after abo...

...on where it is appropriate to apply it. In the meantime, I would suggest that BFGS or L-BFGS-B are the closest options in optim() and generally perform quite well. There are updates to BFGS and CG on CRAN in the form of Rvmmin and Rcgmin which are all-R implementations with box constraints too. UCMINF is a very similar implementation of the unconstrained algorithm that seems to have the details done rather well -- though BFGS in optim() is based on my work, I actually find UCMINF often does better. There's also nlm and nlminb. Via optimx() one can call these, and also some other minimize...

...q vector I want to determine: w = argmin (a - d(w))' A (a - d(w)) where a is a 1xK marix, A is the covariance matrix of vector a, d(w) is a 1xK vector which parameters are functions of parameters d, o1 .. op, m1 .. mq. Is there some function to solve this problem easily? I know optim() and ucminf() for one-dimensional optimization (I believe). Are there some tools for such n-dimensional problem? Kind regards, C. -- -- View this message in context: http://r.789695.n4.nabble.com/Optimization-n-dimension-matrix-tp3490772p3490772.html Sent from the R help mailing list archive at Nabble.com.

Hi, I would like to write a function that finds parameters of a log-normal distribution with a 1-alpha CI of (x_lcl, x_ucl): However, I don't know how to optimize for the two unknown parameters. Here is my unsuccessful attempt to find a lognormal distribution with a 90%CI of 1,20: prior <- function(x_lcl, x_ucl, alpha, mean, var) { a <- (plnorm(x_lcl, mean, var) - (alpha/2))^2 b

...he following method: install.packages("optimx", repos="http://R-Forge.R-project.org") I have received the following information: package 'numDeriv' successfully unpacked and MD5 sums checked package 'BB' successfully unpacked and MD5 sums checked package 'ucminf' successfully unpacked and MD5 sums checked package 'Rcgmin' successfully unpacked and MD5 sums checked package 'Rvmmin' successfully unpacked and MD5 sums checked package 'minqa' successfully unpacked and MD5 sums checked package 'setRNG' successfully unpacke...

Hi, Currently I am trying to solve a minimization problem using optim as method Nelder-Mead. However, Neldel-Mead needs many iterations until it finally converges. I have set $control.trace and $control.report such that I can see the value of the function at each iteration. I do see that I set the convergence criteria to strict in the sense that the function value does not change much. However,