search for: nelder

Hi, I have written an R translation of C.T. Kelley's Matlab version of the Nelder-Mead algorithm. This algorithm is discussed in detail in his book "Iterative methods for optimization" (SIAM 1999, Chapter 8). I have tested this relatively extensively on a number of smooth and non-smooth problems. It performs well, in general, and it almost always outperforms optim...

Dear list,   I am looking for an R-only implementation of a Nelder-Mead process that can find local maxima of a spatially distributed variable, e.g. height, on a spatial grid, and outputs the coordinates of the new point during each evaluation. I have found two previous threads about this topic, and was wondering if something similar has been implemented since tho...

Dear UseRs, Is there a way to define the lower-upper bounds for parameters fitted by optim using the Nelder-Mead method ? Thanks, Arnaud [[alternative HTML version deleted]]

Greetings! I want to follow the evolution of a Nelder-Mead function minimisation (a function of 2 variables). Hence each simplex will have 3 vertices. Therefore I would like to have a function which can output the coordinates of the 3 vertices after each new simplex is generated. However, there seems to be no way (which I can detect) of extracting th...

...method but it stopped regularly before to reach a true mimimum. It was not a problem with limit of iterations, just a local minimum. I was able sometimes to reach better minimum using several rounds of optim(). Then I moved to optimx() to do the different optim rounds automatically using "Nelder-Mead" and "BFGS" methods I find a huge time difference using system.time() based on the order of these both methods: > snb # "Nelder-Mead" and "BFGS" ??? user?? system? elapsed 1021.656??? 0.200 1021.695 > sbn # "BFGS" and "Nelder-Mead&q...

All, In looking at `optim', it doesn't appear that it is possible to impose nonlinear constraints on Nelder- Mead. I am sufficiently motivated to try to code something in C from scratch and try to call it from R.... Does anyone have some good references to barrier and/or penalization methods for Nelder-Mead? I would ideally like some papers with pseudocode for method(s) that are in some sense optimal...

Dear all, I?m having some problems getting optim with method="Nelder-Mead" to work properly. It seems like there is no way of controlling the step size, and the step size seems to depend on the *difference* between the initial values, which makes no sense. Example: f=function(xy, mu1, mu2) { print(xy) dnorm(xy[1]-mu1)*dnorm(xy[2]-mu2) }...

...llowing code works for some users, however my code crashes on the chol. Any suggestions? > mycop <- tCopula(param=0.5, dim=8, dispstr="ex", df=5) > x <- rcopula(mycop, 1000) > myfit <- fitCopula(x, mycop, c(0.6, 10), optim.control=list(trace=1), method="Nelder-Mead") Nelder-Mead direct search function minimizer function value for initial parameters = -1747.582044 Scaled convergence tolerance is 2.6041e-05 Stepsize computed as 1.000000 Error in chol(x, pivot = FALSE) : the leading minor of order 2 is not positive definite Kevin D. Oden...

...a reasonable, optimum, and seems to do so consistently --- i.e. it gets essentially the same estimates irrespective of starting values. We have plotted the log likelihood surface and it appears smooth and relatively innocuous. The phenomenon only occurs with the "L-BFGS-B"; the default (Nelder-Mead simplex) method, with a heavy penalty for violating constraints, seems to work just fine. So we can get solutions; it just makes me uneasy that there's this funny going on. Can anyone shed any light on what the problem is? I have enclosed below code to reproduce the phenomenon. It is p...

...rep(0, 4) BBsolve(par = p0, fn = mgf_gammasum) dfsane(par = p0, fn = mgf_gammasum, control = list(trace = FALSE)) sane(par = p0, fn = mgf_gammasum, control = list(trace = FALSE)) and got the error message: > BBsolve(par = p0, fn = mgf_gammasum) Error in optim(par = par, fn = U, method = "Nelder-Mead", control = list(maxit = 100),  :   function cannot be evaluated at initial parameters Error in optim(par = par, fn = U, method = "Nelder-Mead", control = list(maxit = 100),  :   function cannot be evaluated at initial parameters Error in optim(par = par, fn = U, method =...

...uences/R/R1593_filtered.data",3.48)) + # sum(abs(localShifts))*lambda error <- sum(abs(localShifts))*lambda error # return the error to be minimized } Then I call optim: par <- seq(length=9, from=0, by=0) lambda <- 1/sqrt(147) optim(par, errorFunction, gr=NULL, method="Nelder-Mead", hessian=FALSE, globalShift, "/home/sarah/Semesterarbeit/Sequences/R/R1593_filtered.data", experimentalPI=3.48, lambda = lambda) The output is: $par [1] 0.56350964 0.56350964 0.56350964 0.56350964 0.00000000 -0.29515957 [7] 0.00569937 0.32543297...

...sigma <- sum((LT - TAN(edad,f,c,a,d))^2) / N + logl <- (N/2)*log(sigma) + (sum((LT - TAN(edad,f,c,a,d))^2) / (2*sigma)) + } > ini.pars <- list(f=5.91e-05,c=-0.41732,a=0.009661,d=846.7179) > library(stats4) > erizo.mle <- mle(start= ini.pars, minuslogl = loglike, method="Nelder-Mead", control = list(maxit=1500, trace=TRUE)) Nelder-Mead direct search function minimizer function value for initial parameters = 1159.477620 Scaled convergence tolerance is 1.72776e-05 Stepsize computed as 84.671790 BUILD 5 3165.307359 1159.477620 . . . HI-REDUCTION 303...

...g R to do functional outlier detection (using PCA to reduce to 2 dimensions - the functional boxplot methodology used in the Rainbow package), and using Hscv.diag function to calculate the bandwidth matrix where this line of code is run: result <- optim(diag(Hstart), scv.mat.temp, method = "Nelder-Mead", control = list(trace = as.numeric(verbose))) Within the optim function, there is a call to an external C function: .External2(C_optim, par, fn1, gr1, method, con, lower, upper) Where Par = (0.339, 0.339), fn1 = function (diagH) { H <- diag(diagH) %*% diag(diagH) if (default.bfla...

Hi, I'm having some difficulties formulating this question. But what I want, is to extract the options associated with a parameter for a function. e.g. method = c("Nelder-Mead", "BFGS", "CG", "L-BFGS-B", "SANN") in the optim function. So I would like to have a vector with c("Nelder-Mead", "BFGS", "CG", "L-BFGS-B", "SANN") Or for instance the 'method' in the dist...

...his noisy and smoothed 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 = pracm...

Hi, am very new to R and I've written an optim function, but can't get it to work least.squares.fitter<-function(start.params,gr,low.constraints,high.constraints,model.one.stepper,data,scale,ploton=F) { result<-optim(par=start.params,method=c('Nelder-Mead'),fn=least.squares.fit,lower=low.constraints,upper=high.constraints,data=data,scale=scale,ploton=ploton) return(result) } least.squares.fitter(c(2,2),c(0,0),c(Inf,Inf),ricker.one...

...) { out <- lsoda(Dose/Vd,time,mm.model,parms=c(Vm=Vm,Km=Km,Vd=Vd), rtol=1e-8,atol=1e-8) out[,2] } objfun <- function(par) { out <- modfun(PKindex$time,par[1],par[2],par[3]) sum((PKindex$conc-out)^2) } fit <- optim(c(10,1,80),objfun, method="Nelder-Mead) print(fit$par) [1] 10.0390733 0.1341544 34.9891829 #--Km=0.1341544,wrong value-- #-----wrong model definiens-------- #-----Km should not divided by Vd-- PKindex<-data.frame(time=c(0,1,2,4,6,8,10,12,16,20,24), conc=c(8.57,8.30,8.01,7.44,6.88,6.32,5.76,5.20,4.08,2.98,1.89)) mm.mod...

...tlab program into R. The R code works almost all the time, but about 4% of the time R's optim function gets stuck on a local minimum whereas matlab's fminsearch function does not (or at least fminsearch finds a better minimum than optim). My understanding is that both functions default to Nelder-Mead optimization, but what's different about the two functions? Below, I've pasted the relevant default options I could find. Are there other options I should to consider? Does Matlab have default settings for reflection, contraction, and expansion, and if so what are they? Are there ot...

Hi R users, I am using the optim funciton to maximize a log likelihood function. My code is as follows: p<-optim(c(-0.2392925,0.4653128,-0.8332286, 0.0657, -0.0031, -0.00245, 3.366, 0.5885, -0.00008, 0.0786,-0.00292,-0.00081, 3.266, -0.3632, -0.000049, 0.1856, 0.00394, -0.00193, -0.889, 0.5379, -0.000063, 0.213, 0.00338, -0.00026, -0.8912, -0.3023, -0.000056), f,

Dear R-users, I am trying to port to R something that I wrote in Matlab to perform model parameter optimization using the Nelder-Mead simplex method (fminsearch). I read the help on ?optim (which seems to be the way to go) as well as a bunch of posts on the topic, but I would like to make sure about something before I spend to much time trying to reproduce something that is not possible. The Matlab fminsearch has some nice f...