similar to: constrOptim doesn´t send arguments to optim!(?)

Dear all, There appears to be a bug in how constrOptim handles ... arguments that are suppose to be passed to optim, according to the documentation. This means you can't get the hessian to be returned, for example (so this is a real problem, and not just a question of mistaken documentation). Looking at the code, it appears that a call to the user-defined f includes the ..., when the ...

For a solution that does not require any change to the original function being optimized, the following one-liner could be used, which converts existing functions to functions that return only the first element: returnFirst <- function(fun) function(...) do.call(fun,list(...))[[1]] Example: fr <- function(x) { ## Rosenbrock Banana function x1 <- x[1] x2 <- x[2] ans

How can I use a function with some additional input parameters in constrOptim? For example, something like fr <- function(x,a) { ## Rosenbrock Banana function x1 <- x[1] x2 <- x[2] a * (x2 - x1 * x1)^2 + (1 - x1)^2 } where the optimum is to be found w.r.t. x. Calling optim(c(-1.2,1), fr, NULL, a=100) works as expected, but I fail to provide the a=100 in the constrained case:

Dear List, I am using constrOptim to solve the following fr1 <- function(x) { b0 <- x[1] b1 <- x[2] ((1/(1+exp(-b0+b1))+(1/(1+exp(-b0)))+(1/(1+exp(-b0-b1)))))/3 } As you can see, my objective function is ((1/(1+exp(-b0+b1))+(1/(1+exp(-b0)))+(1/(1+exp(-b0-b1)))))/3 and I would like to solve for both b0 and b1. If I were to use optim then I would derive the gradient of the

Dear List, I have the code below, where I am using the constrained optimisation package, 'constrOptim.nl' to find the values of two values, b0 and b1. I have no problems when I enter further variable information DIRECTLY into the functions, fn, and heq. In this instance I require fn to have -0.0075 appended to it, and in the case of heq, h[1] has -0.2. library(alabama)

Dear friends. I am using function constrOptim(c(0.5,0.3,0.5), fit.error, fit.error.grr, ui=-1*ui,ci=-1*ci) and I am confronted with error message "initial value not feasible" I plug in the initial value of (0.5,0.3,0.5) to function fit.error and fit.error.grr and have pretty reasonable result. I inequality "ui %*% theta - ci >= 0" as suggested in the R manual and it is

Dear Friends. I found something very puzzling with constOptim(). When I change the parameters for ConstrOptim, the error messages do not seem to be consistent with each other: > constrOptim(c(0.5,0.3,0.5), f=fit.error, gr=fit.error.grr, ui=ui,ci=ci) Error in constrOptim(c(0.5, 0.3, 0.5), f = fit.error, gr = fit.error.grr, : initial value not feasible > constrOptim(c(0.5,0.9,0.5),

Hi All, I'm trying to do the following constrained optimization example. Maximize x1*(1-x1) + x2*(1-x2) + x3*(1-x3) s.t. x1 + x2 + x3 = 1 x1 >= 0 and x1 <= 1 x2 >= 0 and x2 <= 1 x3 >= 0 and x3 <= 1 which are the constraints. I'm expecting the answer x1=x2=x3 = 1/3. I tried the "constrOptim" function in R and I'm running into some issues. I first start off

I've moved this from r-help to r-bugs. If you reply, please be careful that replies go to the right place: r-bugs if your comment is specifically about the bug (and it contains the PR# in the subject that will be added when this is cc'd to r-devel), r-devel if general discussion, not both. On Wed, 14 Jul 2004 10:01:45 -0400, "Roger D. Peng" <rpeng@jhsph.edu> wrote :

Dear R users, I?m a graduate students and in my master thesis I must obtain the values of the parameters x_i which maximize this Multinomial log?likelihood function log(n!)-sum_{i=1]^4 log(n_i!)+sum_ {i=1}^4 n_i log(x_i) under the following constraints: a) sum_i x_i=1, x_i>=0, b) x_1<=x_2+x_3+x_4 c)x_2<=x_3+x_4 I have been using the ?ConstrOptim? R-function with the instructions

Okay, looking at the docs, then it's not a bug, since the "..." argument is not actually documented as "other arguments passed to f or grad". However, that *is* how it's document in `optim', so one can see how this might cause some confusion. Now, it's not clear to me which other arguments need to be passed to `optim' except perhaps `hessian'. Am

Hello, the hot key assigned to a MENU BEGIN (via MENU LABEL) doesn't cause the submenu to be entered automatically when MENU IMMEDIATE is used (at previous level). Here's a patch over syslinux 6.03. Patch was tested on Debian. Regards Dany *Sample config* # hot keys: S,1,2 are immediate (screen flash), but not E MENU IMMEDIATE LABEL standard MENU LABEL ^Standard MENU BEGIN MENU LABEL

Hi, i have a function: zz<- (constrOptim(c(.5,0), fr, grr, ui=rbind(c(-1,0),c(1,-1)), ci=c(-0.9,0.1))) i can get the result by using command (for example): zz$par now if i can use multicore: zz<-parallel(constrOptim(c(.5,0), fr, grr, ui=rbind(c(-1,0),c(1,-1)), ci=c(-0.9,0.1))) result < collect(zz) i cant get my the result: result$par because multicore add process id. for example:

Dear all, I have used optim a lot in contexts where it would useful to be able to iterate function myfun that, in addition to the primary objective to be minimized ('minimize.me'), could return other values such as alternative metrics of the minimization, informative intermediate values from the calculations, etc. myfun <- function() { ... return(list(minimize.me = minimize.me, R2 =

Dear friends. I use ConstrOptim( ) and got error message "initial value not available". My understanding of "initial value not available" is that one of the following 3 cases happens: 1.The objective function is not well defined at the point of the initial value. 2. The differentiation of the objective function is not well defined at the point of the initial value. 3. The

Dear list, The following example of constrOptim() where the initial point is the solution shows that the component counts is not a two-element vector as documented in the man page. constrOptim(c(1,1), fr, grr, ui = diag(2), ci = c(0,0)) Does anyone have the same behavior? A possible solution is to put line 69 in constrOptim.R before the first possible break line 67. Regards, Christophe

I have a function myFunction(beta,x) where beta is a vector of coefficients and x is a data frame (think of it as a matrix). I want to optimize the function myFunction() by ONLY changing beta, i.e. x stays constant, with 4 constraints. I have the following code (with a separate source file for the function): rm(list=ls()) source('mySourceFile')

From: Quan Xu <quan.xu0 at gmail.com> To reduce the cost of poll, we introduce three sysctl to control the poll time when running as a virtual machine with paravirt. Signed-off-by: Yang Zhang <yang.zhang.wz at gmail.com> Signed-off-by: Quan Xu <quan.xu0 at gmail.com> --- Documentation/sysctl/kernel.txt | 35 +++++++++++++++++++++++++++++++++++ arch/x86/kernel/paravirt.c

From: Quan Xu <quan.xu0 at gmail.com> To reduce the cost of poll, we introduce three sysctl to control the poll time when running as a virtual machine with paravirt. Signed-off-by: Yang Zhang <yang.zhang.wz at gmail.com> Signed-off-by: Quan Xu <quan.xu0 at gmail.com> --- Documentation/sysctl/kernel.txt | 35 +++++++++++++++++++++++++++++++++++ arch/x86/kernel/paravirt.c

There is a contradiction between what the help page says and what constrOptim actually does with the constraints. The issue is what happens on the boundary. The help page says The feasible region is defined by ?ui %*% theta - ci >= 0?, but the R code for constrOptim reads if (any(ui %*% theta - ci <= 0)) stop("initial value not feasible") The following example