similar to: Optimization with nonlinear constraints

Hello. I have some problems, when I try to model an optimization problem with some constraints. The original problem cannot be solved analytically, so I have to use routines like "Simulated Annealing" or "Sequential Quadric Programming". But to see how all this works in R, I would like to start with some simple problem to get to know the basics: The Problem: min f(x1,x2)=

Dear All, I am having trouble in using R function "constrOptim" to do constraint optimization. It seems that "constrOptim" calls function "optim" when it does the optimization, and "optim" allows us to set "method" to be "SANN" if we want to use simulated annealing. In "optim", the function allows us to set gradient to be

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 all, I'm trying to fit a nonlinear (logistic-like) regression, and I'd like to get some recommendations for which package to use. The expression I want to fit is something like: y ~ A * exp(X * Beta1) / (1 + exp(-(x + X * Beta2 - xmid)/scal)) Basically, it's a logistic function, but I want to be able to modify the saturation amplitude by a few parameters (Beta1) and shift the

Hello list, I am dealing with a noisy function (gradient,hessian not available) with simple boundary constraints (x_i>0). I've tried constrOptim() using nelder mead to minimize it but it is way too slow and the returned results are not satisfying. simulated annealing is so hard to tune and it always crashes R program in my case. I wonder if there are any packages or functions can do

Hello R community, I am using R for creating a model using optimization. I would like to ask if there is R-function/package for solving the problem below: Minimize sum(abs(exp^(Ai1 x1 + Ai2 x2 + ... + Aim xm - bi) - 1)), for each i = 1, ..., n. subject to Ai1 x1 + Ai2 x2 + ... + Ajm xm - bi <= c, where c is a scalar. (x is a vector of variables, A is nxm matrix, b is a vector)

Dear All, Thank you for the replies to my first thread here: http://r.789695.n4.nabble.com/global-optimisation-with-inequality-constraints-td3799258.html. So far the best result is achieved via a penalised objective function. This was suggested by someone on this list privately. I am still looking into some of the options mentioned in the original thread, but I have been advised that there may

Hi there, I am trying to plot some output from a FORTRAN (ifort) program using R (2.5.1) under batch mode. In the FORTRAN code, I call R in batch mode to execute a script called fig1.R using something like PROGRAM test USE IFPORT IMPLICIT NONE DO !Some function which makes an output file called ~/fortran_output.txt CALL myfunc() !System call to R plotting routine CALL SYSTEM

I want to get some "simple" logic regression examples to work before exploring a hard problem. I can get results, but I'm having some problems using "cat" to save the logic regression equation to a disk file. Consider this: # Simple Logic Regression Example # efg, 23 Feb 2005 library(LogicReg) # Create simulated data with known logic equation: # "noise"

Hi, As I mentioned some time ago on the mailing list, I'm working on the implementation of the Sarkar's Extended Linear Scan algorithm for LLVM. For testing and debugging of this algorithm, I need some good test-cases that check different functionalities of the register allocator, e.g.: - test-cases involving a lot of spilling - test-cases using pre-colored registers, e.g. like the EAX

Hi, I'm trying to sketch an LLVM-based implementation of the Extended Linear Scan algorithm, described in this Vivek Sarkar's paper: http://www.cs.rice.edu/~vs3/PDF/cc2007.pdf Sarkar reports that this version of Linear Scan produces better code than graph-coloring regallocs and is also much faster (15x to 68x). I already started work on the implementation of this algorithm and have a few

Dear all, I'm looking for a way to solve a simple optimization problem with a nonlinear constraint. An example would be max x s.t. y = x * T ^(x-1) where y and T are known values. optim() and constrOptim() do only allow for box or linear constraints, so I did not succedd here. I also found hints to donlp2 but this does not seem to be available anymore. Any hints are welcome,

Hi all, I've got a question on regarding how to find out the duration of an ogg vorbis file. Sorry if it should already be mentioned somewhere in the docs, but I couldn't find out how to do it the best way. So, I can read the [bitrate_nominal] field from the identification header (if it is set), find out the size of the audio data (by subtracting the size of the three headers from the

Hello. Has anyone any idea how a function would look like of a model based bootstrap, when the underlying time series follows an ARIMA(1,1,1)-process? A pure AR-process is no problem, but what is, if the time series need to be differentiated of order one or above and the additional MA-part? Sample code for a series, which follows a pure AR-process: #Series y of 192 observations, which follows

Hi, While profiling LLVM using my test-cases with huge MBBs, I noticed that FoldingSetNodeID operations (ComputeHash,insertion,etc) may become really inefficient for the nodes, which have very many operands. I can give you an example of what is meant by "very many". In my test-case (you can fetch it from here http://llvm.org/bugs/attachment.cgi?id=1275), which is just one HUGE MBB

-----Original Message----- Message: 6 Date: Mon, 20 Jan 2003 01:11:24 +0100 From: Martin Michlmayr <tbm at cyrius.com> To: r-help at stat.math.ethz.ch Subject: [R] quadratic trends and changes in slopes I'd like to use linear and quadratic trend analysis in order to find out a change in slope. Basically, I need to solve a similar problem as discussed in

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 David, --- David Greene <dag at cray.com> schrieb: > On Thursday 31 January 2008 07:05, Roman Levenstein wrote: > > > I already started work on the implementation of this algorithm and > have > > a few hopefully rather simple questions: > > Roman, > > I'm excited to hear that you are working on this algorithm. Do you > plan to contribute it

On Jan 31, 2008, at 5:05 AM, Roman Levenstein wrote: > Hi, > > I'm trying to sketch an LLVM-based implementation of the Extended > Linear Scan algorithm, described in this Vivek Sarkar's paper: > http://www.cs.rice.edu/~vs3/PDF/cc2007.pdf > Sarkar reports that this version of Linear Scan produces better code > than graph-coloring regallocs and is also much faster (15x

I'm preparing some code to compute the optimal geometry of stressed solids. The core of the calculations is the optimization of elastic energy using the simulated annealing method implemented in the R optim() rutine. I've defined a function to compute this "energy" scalar (the fn parameter for optim) and prepared a list with the arrays defining the geometry and the elastic