similar to: hessian in constrained optimization (constrOptim)

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 helpers, I wrote a code which estimates a multi-equation model with generalized least squares (GLS). I can use GLS because I know the covariance matrix of the residuals a priori. However, it is a bit slow and I wonder if anybody would be able to point out a way to make it faster (it is part of a bigger code and needs to run several times). Any suggestion would be greatly appreciated. Carlo

Dear helpers, I am using R version 2.5.1 to estimate a multinomial logit model using my own maximum likelihood function (I work with share data and the default function of R cannot deal with that). However, the computer (I have an Athlon XP 3200+ with 512 GB ram) takes quite a while to estimate the model. With 3 categories, 5 explanatory variables and roughly 5000 observations it takes 2-3 min.

Hi, i have made a code for optimizing a function using "constrOptim". i need hessain matrix of the parameters. how could i get hessain matrix when i will use "constrOptim"? May i get get any help from anyone? thank you in advance. Kanak Choudhury. [[alternative HTML version deleted]]

Dear all, I am writing an R code to fit a Bayesian mixed logit (BML) via MCMC / MH algorithms following Train (2009, ch. 12). Unfortunately, after many draws the covariance matrix of the correlated random parameters tend to become a matrix with almost perfect correlation, so I think there is a bug in the code I wrote but I do not seem to be able to find it.. dull I know. Has anybody written a

Hi, Is there any way to get the hessian matrix from the "constrOptim" function without supplying gradient function? Thanks. --------------------------------- Bring words and photos together (easily) with [[alternative HTML version deleted]]

Dear Helper, I used "constrOptim.nl" and got the value of par. The estimations looks good even if the number of iterations is only 16. But the values of hessian and convergence are both "NULL". I tested the objective function and gradient function by "optim" and didn't see any problem there. With these functions, "optim" gives the convergence value

Hi, Use the `auglag' function in "alabama" if you want to get the Hessian at convergence. This typically tends to perform better than `constrOptim.nl'. Also, `constrOptim.nl' does not compute the Hessian. You should not specify method="L-BFGS-B". The default method "BFGS" is better in this setting. Hope this helps, Ravi

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

Dear all R users, Is there any way to calculate hessian matrix of a given function at any given point? Regards [[alternative HTML version deleted]]

Hi Everyone, I'm trying to minimize a function using constrOptim with the simulated annealing method SANN. If I understand constrOptim well, it basically passes most of its arguments to optim while somehow enforcing the constraints. My problem is, that since SANN does not need gradients, when using optim with SANN, the gr argument of optim is used to specify a function to create the next

Dear helpers, Does anyone know about a package or a function that allows to estimate Multivariate Markov-Switching Models, like MS-VAR as introduced by Krolzig(1997) with R ? Thanks a lot!! Carlo

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 %*%

Hi, I'm having trouble using the constrOptim function to generate the 9-component vector argmin of the function ELfsds: ELfsds <- function(pvechat){ LG=0 for(i in 1:9){ LG=LG+log(pvechat[i]) } return(-LG) } with accompanying gradient function: gradfunc <- function(thetavec){ g=1/(9*thetavec) return(g) } The constraints on the optimization problem are: 1 - components of

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')

Hi everybody, please, could you give me help ? I scanned the help archives and didn't found hints... I want to solve a large sparse linear system subjected to an inequality constrains (all solutions positive) and an equality constrain (all solutions sum to 1), thus I tried to fool constrOptim using: x[1] + 0 + ... + 0 >= 0 ... 0 + 0 + ... + x[n] >= 0 x[1] + x[2] + ... +

Hello, I got a question with the R function constrOptim. >From the R help, it says that the return values of "constrOptim" are the same as "optim". For the return value "convergence" of the function "optim", the values should be 0, 1, 10, 51 and 52. See http://www.maths.lth.se/help/R/.R/library/stats/html/optim.html When I use constrOptim, I get

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 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

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: