similar to: Re: [R] constrOptim and function with additional parameters? (PR#7088)

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

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:

Hi, I think that there something wrong with the 'constrOptim' max/minimization function because she doesn?t send extra arguments to 'optim' call. Fact: When I use optim in a f(x,theta)-like function, everything goes ok. But using constrOptim with the same function leads to error... Proof: Make a small change in the 'Rosenbrock Banana function' (taken from the Examples

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 ...

Hi, I apologize for the long message but the problem I encountered can't be stated in a few lines. I am having some problems with the function constrOptim. My goal is to maximize the likelihood of product of K multinomials, each with four catagories under linear constraints on the parameter values. I have found that the function does not work for many data configurations. #The likelihood

Hello, I am using constrOptim to maximize a likelihood function (the values of my parameter vector must be between zero and one and must sum up to <=1). I am getting the error 'initial value in 'vmmin' is not finite'. I've tracked it down to a problem in the function 'R' defined within the constrOptim function. It is performing a check on my values, and its not

Hello, I'm trying to run constrOptim. It returns to me an error about the fact that constraints arguments (ui and ci) are non compatibles: > optout= constrOptim(startparams, f=ImpulseSS, grad=grImpulse, ui=UI, ci=CI, data=gexp[k,], t=t) Error in ui %*% theta : non-conformable arguments I would like to point out that I can calculate that product in the command line: > UI %*%

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

Hello. I had previously posted a question concerning the optimization of a nonlinear function conditional on equality constraints. I was pointed towards the contrOptim function. However, I do not understand the syntax of this function with respect to specifying the constraints and so I don’t know if it is what I need. The command is: constrOptim(theta, f, grad,ui,ci,…). “theta” is the

This is not so much a question as a contribution, but comments are welcome. Comments: 1) thank you very much to Paul Smith in the post https://stat.ethz.ch/pipermail/r-help/2008-March/157249.html This is intended to build on that example with something more complex than a 2x2 set of constraints 2) "L-BFGS-B" does not appear to work in optimConst Problem: let's

Full_Name: Haobo Ren Version: 2.1.1 OS: Windows 2000 Submission from: (NULL) (192.11.226.116) When running constrOptim, there is error message Error: subscript out of bounds

Dear R-users, In the function constrOptim there is an option to get an approximation to the hessian of the surrogate function R at MLE by declaring hessian=TRUE in the calls to the function optim. I would like to ask if it is advisable to get an approximate hessian for the funcrion f as follows: f''(theta)=R''(theta|theta_k)-B''(theta) where

Hello All, I am stuck in the following problem. Cexpt=c(0,25,50,100,150,300,250,125,40) t=c(0,0.2,0.4,0.6,1,4,8,12,24) theta0= vector of 6 parms (My initial parameter) A=Constraint matrix (hopefully 6*6) B= Constraint vector of length 6) Cfit=function(t,theta){ J(t)=function(theta,t) Cfit=function(J(t),constant) return(Cfit) } loss=function(theta,t,Cexpt) {

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')

Code in constrOptim() (R-2.0.0, package stats): if (any(ui %*% theta - ci <= 0)) stop("initial value not feasible") but the help page tells us in Section "Details": "The feasible region is defined by ui %*% theta - ci >= 0." Uwe Ligges --please do not edit the information below-- Version: platform = i386-pc-mingw32 arch = i386 os =

Dear helpers, I am using the function "constrOptim" to estimate a model with ML with an inequality constraint using the option method='Nelder-Mead'. When I specify the option: hessian = TRUE I obtain the response: Error in f(theta, ...) : unused argument(s) (hessian = TRUE) I guess the function "constrOptim" does not allow this argument which, on the other hand, is

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

Hello, I have the following problem: I have a set of n matrix equations in the form of : [b1] = [A] * [b0] [b2] = [A] * [b1] etc. vertical vectors [b0], [b1], ... are GIVEN. We try to estimate matrix A. As there are many equations (more than cells in matrix A) the system has no solutions. A is transition matrix (stochastic matrix) or markov process, so the sum of each row = 1 and each entry is

Dear helpers, I am using constrOptim to minimize a function subject to inequality constraint. It works well when the number of parameters to optimize is low (e.g. 4) but when they are more (e.g. 10) it does not produce the expected results. The function is minus the determinant of a binomial logit model with one explanatory variable. Calling ?xeta? the vector of explanatory variables 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)