similar to: Nonlinear Optimization

Hi, I have a couple of quick questions regarding R. 1) I have a ".First" function that automatically loads the quadprog package into the workspace. The .First function resides in R and is only saved if I save the workspace. The exact function is as follows: .First<-function() { library(quadprog) } Is there any way that this function can be saved outside of R? That is, is there

Hi, Quick question on reading data. I am running simulations but want to allow the user the option to define the number of simulations. How can I have R read-in user data entered from the keyboard? Is there a difference for reading in numeric and character data? For example, I am trying to write the following in R: Enter Number of Iterations? <<<the user then enters a number say Y

Hi, I have recently started using R again (switched from MatLab) and have a question regarding programming. How can I set up a file that will run several lines of R code? For example, in Fortran and DOS this used to be done via a batch file, and in MatLab I would write the code and save it in a script file, e.g., Test.m. An example of what I am trying to do is the following:

Hello. I'm trying to solve a quadratic programming problem of the form min ||Hx - y||^2 s.t. x >= 0 and x <= t using solve.QP in the quadprog package but I'm having problems with Dmat not being positive definite, which is kinda okay since I expect it to be numerically semi-definite in most cases. As far as I'm aware the problem arises because the Goldfarb and Idnani method first

Hi All, I'm trying to do the following constrained optimization example. Maximize x1*(1-x1) + x2*(1-x2) + x3*(1-x3) s.t. x1 + x2 + x3 = 1 x1 >= 0 and x1 <= 1 x2 >= 0 and x2 <= 1 x3 >= 0 and x3 <= 1 which are the constraints. I'm expecting the answer x1=x2=x3 = 1/3. I tried the "constrOptim" function in R and I'm running into some issues. I first start off

Dear list members, I am trying to get information on how to fit a linear regression with constrained parameters. Specifically, I have 8 predictors , their coeffiecients should all be non-negative and add up to 1. I understand it is a quadratic programming problem but I have no experience in the subject. I searched the archives but the results were inconclusive. Could someone provide suggestions

Dear All I am dealing at the moment with optimization problems with nonlinear constraints. Regenoud is quite apt to solve that kind of problems, but the precision of the optimal values for the parameters is sometimes far from what I need. Optim seems to be more precise, but it can only accept box-constrained optimization problems. I read in the list archives that optim can also be used with

?s 19:36 de 27/03/2025, Daniel Lobo escreveu: > My code is to minimize the objective function > > therefore, shouldnt I expect that > > StartingValue = c(0.12, 0.04, 0.07, 0.03, 0.06, 0.07, 0.07, 0.04, 0.09, > 0.08, 0.02, 0.02, 0.03, 0.06, 0.02, 0, 0.07, 0.05, 0.02, 0.02, 0.02) > Fn(q1$par) < Fn(StartingValue) > ## FALSE > > Below is the corrected code that can

Hi Duncan, Thanks for your comment, I agree with that. But, how it can be justified that an Optimizer gives a result which is inferior to the starting value? At most, resulting value can remain at the same level, isnt it? On Fri, 28 Mar 2025 at 14:34, Duncan Murdoch <murdoch.duncan at gmail.com> wrote: > I haven't run your code, but since Kendall correlation is based on >

Hi, I am trying to use the nls() function to closely approximate a vector of values, colC and I'm running into trouble. I am not sure how if I am asking the program to do what I think its doing, because the same minimization in Excel's Solver does not run into problems. If anyone can tell me what is going wrong, and why I'm getting a singular convergence(7) error, please tell me. I

Hi, I am relatively new to R and am trying to solve two simultaneous nonlinear equations in two variables numerically, and was wondering if anyone knew if any of the packages could do that. An alternative is writing my own code using Newton-Raphson; I did that but was not able to get good convergence. Any ideas please? Thanks Yogesh [[alternative HTML version deleted]]

At the risk of ridicule for my deficient linear algebra skills, I ask for help using the solve.QP function to do portfolio optimization. I am trying to following a textbook example and need help converting the problem into the format required by solve.QP. Below is my sample code if anyone is willing to go through it. This problem will not solve because it is not set up properly. I hope I

Hi, I have below minimization problem MyDat = structure(list(c(50L, 0L, 0L, 50L, 75L, 100L, 50L, 0L, 50L, 0L, 25L, 50L, 50L, 75L, 75L, 75L, 0L, 75L, 75L, 75L, 0L, 25L, 75L, 75L, 0L, 75L, 100L, 0L, 25L, 100L), c(75L, 0L, 0L, 50L, 100L, 50L, 75L, 75L, 100L, 25L, 0L, 25L, 100L, 0L, 50L, 0L, 25L, 25L, 100L, 75L, 0L, 0L, 0L, 50L, 0L, 75L, 75L, 0L, 50L, 25L), c(50L, 0L, 0L, 0L, 100L, 25L, 0L, 0L,

Hi everybody, I'm using Windows XP Prof, R 2.5.1 and a Pentium 4 Processor. Now, I want to solve a quadratic optimization program (Portfolio Selection) with the quadprog package I want to minimize (\omega'%*%\Sigma%*%\omega) Subject to (1) \iota' %*% \omega = 1 (full investment) (2) R'%*%\omega = \mu (predefined expectation value) (3) \omega \ge 0 (no short sales). Where

Hello. I have searched the archives but have not found anything. I need to solve a constrained optimisation problem for a nonlinear function (“maximum entropy formalism”). Specifically, Optimise: -1*SUM(p_ilog(p_i)) for a vector p_i of probabilities, conditional on a series of constraints of the form: SUM(T_i*p_i)=k_i for given values of T_i and k_i (these are constraints on

Dear list, I am trying to follow an example that estimates a 2x2 markov transition matrix across several periods from aggregate data using restricted least squares. I seem to be making headway using solve.QP(quadprog) as the unrestricted solution matches the example I am following, and I can specify simple equality and inequality constraints. However, I cannot correctly specify a constraint

Readers, Using version 251 I tried the following command: lm(y~a+b,data=datafile) Resulting in, inter alia: ... coefficients (intercept) a 1.2 3.4 Packages installed: acepack ace() and avas() for selecting regression transformations adlift An adaptive lifting scheme algorithm akima Interpolation of irregularly spaced

Hi, I would like to estimate a quadratic almost ideal demand system in R which is estimated usually by nonlinear seemingly unrelated regression. But there is no such function in R yet but it is readily available in STATA (nlsur), see B. Poi (2008): Demand-system estimation: Update, Stata Journal 8(4). Now I am thinking, what is quicker learning to "program" STATA which seems not really

I haven't run your code, but since Kendall correlation is based on ranks, your Fn is probably locally constant with jumps when the ranks change. That's a really hard kind of function to maximize, and the algorithm used by fmincon is not appropriate to do it. Sorry, but I don't know if there is an R function that can do constrained discrete maximization. Duncan Murdoch On

Dear all, I am looking for a R-function that performs nonlinear constraint optimization (where the objective function and the constraints are allowed to be nonlinear). More specifically, I am trying to figure out whether there is an equivalent function of NAG fortran library' "E04UCF" or matlab's "fmincon" in R. Any help is greatly appreciated. Thank you, Sunduz