similar to: non-linear contrained optimization

>>> What were your biggest misconceptions or >>> stumbling blocks to getting up and running >>> with R? Easy. I terms of materials I have been unable to find good books that introduce users to R from the perspective of someone familiar only with packages like SPSS or STATA, or not familiar with statistics packages at all. Even introduction texts use jargon

Previous versions have this question have partially bounced. I apologize if parts of this are showing up multiple times on the list. Another try ... There was at one time an R package called Rdonlp2 for solving constrained nonlinear programming problems. Both the objective function and the constraints could be nonlinear in the decision variables. The package is no longer in the CRAN list.

Dear experts, I'm attempting to solve a constrained optimization problem using the Rdonlp2 package. I created a Lagrange function (L=f(x)-lambda(g(x)-c)), where x is a vector of 16 parameters. This is what I'm using as objective function in the code below. In addition, I set bounds on these parameters (par.u and par.l). When I run the code, I get the error message shown below. Any idea

Hi Guys, Recently I wrote a package for dealing with Markov Switching Regressions in R and it is included in the Rmetrics project. https://r-forge.r-project.org/projects/rmetrics/ Everything works fine when I use it in computer. But, the package depends on the use of optimization functions from the package Rdonlp2, which is not available on CRAN. So, if I have Rdonlp2 in my laptop (or any

Dear all, I have a question on the use of GAM with repeated measures. My dataset is as follows: - a number of study areas where bird abundance has been determined. Counts have been performed in 3 consecutive years and there were 2 counts per year (i.e. in total 6 counts). - a number of environmental predictors that do not change over year Xi). When using a GLM, a repeated measures design would

Dear List, I'm trying to interpret the results of the Kruskal's Non-metric Multidimensional Scaling algorithm (isoMDS, MASS package). The 'goodness of fit' is reported as "The final stress achieved (in percent)". What does this mean exactly? I've tried to google for an answer but I've not come up with a definitive answer. Regards, Dieter -- Dieter Vanderelst

I can't load Rdonlp2 package. Please support me. Thanks ------------------------------------ Thien An Ho Chi Minh city - VIET NAM [[alternative HTML version deleted]]

Hi. I need some advises on how to use R to find pi (i is the index) with the following objective function and constraint: max (sum i)[ f(ai, bi, pi) * g(ci, di, pi) * Di ] s.t. (sum i)[ f(ai, bi, pi) * Di * pi] / (sum i)[ f(ai, bi, pi) * Di ] <= constant f and g are diffentiable. So, I am thinking of optim with method = "BFGS"? But wonder how to include the

I calculate an anova test in the following way: expdata<-read.table("/home/dorien/UA/meta-music/optimuse/optimuse1-build-desktop/results/results_processedCP", header=TRUE)

I'm looking for an example of a simple R script that impliments a contrained nonlinear function using nlm or optim. I'm not exactly sure how to impliment the constraints within the objective function that is passed to nlm/optim. obj.func <- function( p ) { x(p) <- unconstrained obj function value if( constraint1 > something ) { obj.func <- x(p) } else {

Hi I need advice regarding constraint optimization with large number of variables. I need to solve the following problem max f(x1,...,xn) x1,..xn x1=g1(x1,...,xn) . . xn=gn(x1,...,xn) I am using Rdonlp2 package which works well until 40 variables in my case. I need to solve this problem with over 300 variables. In this case Rdonlp2 is very very slowly. I know

Dear Sir, I installed successfully using the install.packages("Rdonlp2", repos=" http://R-Forge.R-project.org"). I tried on the example which is defined on the Rdonlp help file ,p <- c(-10,10)par.l <- c(0,0); par.u <- c(100,100)lin.u <- 1; lin.l <- 1A <- t(c(1,1))fn <- function(x){ x[1]^2+x[2]^2}ret <- donlp2(p, fn, par.lower=par.l, par.upper=par.u, A=A,

Hi, Based on user input, I wrote a function that creates a list which looks like: > str(list) List of 4 $ varieties: chr [1:12] "temp.26_time.5dagen_biorep.1" "time. 5dagen_temp.26_biorep.2" "temp.18_time.5dagen_biorep.1" "temp.18_time. 5dagen_biorep.2" ... $ temp : Factor w/ 2 levels "18","26": 2 2 1 1 2 2 1 1 1 1 ...

L.S. Since some time there is a new r-project.org site as announced here: https://stat.ethz.ch/pipermail/r-announce/2015/000581.html The logo has changed on the site, but I fail to find a vector graphics file. For the previous logo I used to go to https://svn.r-project.org/R-dev-web/trunk/Logo/ Is there anything similar for the new logo? Many thanks in advance. Kind regards, Tobias --

Hi all, Never really managed to build a for-loop with multiple running variables in an elegant way. Can anybody hint ? See below for an example of what I would like. EXAMPLE a<-c(1,2,3) b<-c("name1","name2","name3") for( number in a, name in b ) { print( number ) ##take a value print( name ) ##and have its name available from a second list } Does R

Hi R, A quick question.... How can I optimize the objective function constrained to quadratic constraints? Which function of R is useful for quadratic constraints? Many Thanks, Shubha This e-mail may contain confidential and/or privileged i...{{dropped:13}}

Dear All, I couple of weeks ago, I’ve asked for a package recommendation for nonlinear optimization. In my problem I have a fairly complicated non-linear objective function subject to one non-linear equality constrain. I’ve been suggested to use the *Rdonlp2* package, but I did not get any results after running the program for 5 hrs. Is it normal to run this type of programs for hours? Also,

Afaik it runs 4.9.15 \- - - mailto:commandline at protonmail.com Joris Lambrecht CyberSecurity and ICT Coach call:?+32 487 558 354 Antwerp,?Belgium https://www.commandline.be \-------- Oorspronkelijk bericht -------- Aan 4 jul. 2020 19:09, Rowland penny via samba < samba at lists.samba.org> schreef: > > > > On 04/07/2020 16:36, commandline at

Hello all, I’m trying to add some data points to a wireframe. X an Y axis are independent variables, Z axis is predicted probability. I’d like to add the original data points on which the predicted probabilities are based to the wireframe. I’ve followed some of the previous post on this but get stuck : ## first part yields the wireframe## setwd("C:/Temp") rnp <-

Hi All, I would like to fill the area under a curve with a gradient of colors. Are there any packages or trick I could use Thanks Stefan Stefan Van Dongen Antwerp [[alternative HTML version deleted]]