similar to: ConstrOptim Function (Related to Constraint Matrix/ui/ci error)

Hi, I am a bit stuck on specifying ui and ci. I have read Lange's book ((1999) Numerical Analysis for Statisticians) to his approach and unfortunately his descriptions were not helpful for me. Here is what I have: ui <- rbind(c(0, -1, 0), c(0, 0, -1)) ci <- c(0, -1, -1)) theta <- c(0.5, 0.5, 0.1) My goal is to feed these into constrOptim

Hi Livia and everyone, Did you ever get a response on this question from last year (Jan 2008)? I am also looking for more explanatory documentation on the ui and ci parameters for the function constrOptim(). The examples provided in the R help and the full reference manual are not working for me. Goodle and Nabble searches have not resulted in any explanation

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 %*%

I'm using the function constrOptim together with the "SANN" method and my objective function (f) has two parameters. One of the parameters needs be into (2^(-10), 2^4) range and the other into (2^(-2), 2^12) range. How can I do it using constrOptim?? Thank you André Rossi Alertas do Yahoo! Mail em seu celular. Saiba mais em http://br.mobile.yahoo.com/mailalertas/

Hi, I am having trouble using constrOptim. My target is to do a portfolio optimization and there some constraints have to be fulfilled. 1) The weight of each share of the portfolio has to be greater than 0 2) The sum of these weights has to be 1 I am able to fulfill either the first or the second constraint but not both. One simple way would be to fulfill the first constraint by using optim as

Hello list reader, I am trying to form some constraints for an optimization I am working on. I think I have understand the use of the constraints in matrix form. I use them like: constr_mat<- -diag(2) constr_vec<- rep(-0.05,2) constr_mat<- rbind(constr_mat, diag(2)) constr_vec<- c(constr_vec, rep(-1, 2)) To get parameters in the interval [-1, 0.05]. (And this works so far) Now I

I am trying to optimize a likelihood function using constrOptim. I know from prior research that, e.g. x1>x2. Is there a way to include that constraint into the optimization routine, i.e. the ci constraint? The examples I found only use absolute numeric values for the constraint and not relative values. My attempts to include it into ci failed: e.g. ci=c(1, x[1]). Am I using the

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

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'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 :

Hello R users,  I am trying to obtain a direct adjusted survival curve. I am sending my whole code (see below). It's basically the larynx cancer data with Stage 1-4. I am using the cox model using coxph option, see the fit3 coxph. When I use the avg.surv option on fit3, I get the following error: "fits<-avg.surv(fit3, var.name="stage.fac", var.values=c(1,2,3,4), data=larynx)

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

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

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

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')

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 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

Well, I would suggest using the code already in place in the survival package. Here is my code for your problem. I'm using a copy of the larynx data as found from the web resources for the Klein and Moeschberger book. larynx <- read.table("larynx.dat", skip=12, col.names=c("stage", "time", "age", "year",

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

Dear R wizards: I am playing (and struggling) with the example in the constrOptim function. simple example. let's say I want to constrain my variables to be within -1 and 1. I believe I want a whole lot of constraints where ci is -1 and ui is either -1 or 1. That is, I have 2*N constraints. Should the following work? N=10 x= rep(1:N) ci= rep(-1, 2*N) ui= c(rep(1, N), rep(-1, N))