similar to: quadprog issues---how to define the constriants

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

I'm having difficulty figuring out how to implement the following set of constraints in Quadprog: 1). x1+x2+x3+x4=a1 2). x1+x2+x5+x6=a2 3). x1+x3+x5+x7=a3 4). x1+x2=b1 5). x1+x3=b2 6). x1+x5=b3 for the problem: MIN (x1-c1)2+(x2-c2)2+...+(x8-c8)2. As far a I understand, "solve.QP(Dmat, dvec, Amat, bvec, meq=0, factorized=FALSE)" reads contraints using an element-by-element

Hi, I'm using the package quadprog to solve the following quadratic programming problem. I want to minimize the function (b_1-b_2)^2+(b_3-b_4)^2 by the following constraints b_i, i=1,...,4: b_1+b_3=1 b_2+b_4=1 0.1<=b_1<=0.2 0.2<=b_2<=0.4 0.8<=b_3<=0.9 0.6<=b_4<=0.8 In my opinion the solution should be b_1=b_2=0.2 und b_3=b_4=0.8. Unfortunately R doesn't find

I would like you consider that the function ecdf could be extended in the following way to handle weights when computing Empirical distribution Functions. There exist particular cases that supports this kind of extension, see for example: Rao, C. R., 1997. Statistic and True. Putting chance to work. World Scientific Publishing. Cox, D. R., 1969. Some Sampling Problems in Technology. New

Hi dears, I expect that Mr Thomas Lumley will read this message. I have data from a complexe stratified survey. The population is divide in 12 regions and a region consist to and urban area and rural one. there to region just with urbain area. stratification variable is a combinaison of region and area type (urban/rural) In rural area, subdivision are sample with probabilties proporionnal to

I forgot to attach the problem data, 'quadprog.Rdata' file, in my prior email. I want to report a following error with quadprog. The solve.QP function finds a solution to the problem below that violates the last equality constraint. I tried to solve the same problem using ipop from kernlab package and get the solution in which all equality constraints are enforced. I also tried an old

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

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

Im trying to do regressions with constraints that the weights are all >=0 and sum(weights) = 1. I've read the archive and have set the problem up with solve.QP and just the non-negativity constraints along the lines of: y as the data vector X as the design matrix D <- t(X) %*% X d <- t(t(y) %*% X) A <- diag(ncol(X)) b <- rep(0,ncol(X)) fit <-

Hi, You can use the projectLinear argument in BB::spg to optimize with linear equality/inequality constraints. Here is how you implement the constraint that all parameters sum to 1. require(BB) spg(par=p0, fn=myFn, project="projectLinear", projectArgs=list(A=matrix(1, 1, length(p0)), b=1, meq=1)) Hope this is helpful, Ravi [[alternative HTML version deleted]]

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

Hello everyone, I have 3 variables Y, X1 and X2. Each variables lies between 0 and 1. I want to do a constrained regression such that a>0 and (1-a) >0 for the model: Y = a*X1 + (1-a)*X2 I tried the help on the constrained regression in R but I concede that it was not helpful. Any help is greatly appreciated -- Thanks, Jim. [[alternative HTML version deleted]]

I have a set of data for US t-bill returns and US stock returns frm 1980-2012. I am trying to bootstrap the data and obtain the minimum variance portfolio and repeat this portfolio 1000 times. However I am unable to get the correct code function for the minimum variance portfolio. When I tried to enter Opt(OriData+1, 1, 5, 0), I get "error:subscript out of bounds" Please help!

I am trying to model counts data from three different sites where the number of zeros differs significantly from one sight to another and also the counts gets bigger in site with few number of zeros considerably, meaning that the k's are different. In my model I am including about 10 covariates to start with, and I have beed attempting to fit a NEGATIVE BINOMIAL MODEL. The problem is the

For my problem I have #Constraints b11<-0 b21<-0 b12<-0 b22<-0 n1>=0 n2>=0 n1<=1 n1<=1 n1+n2=1 In order to use spg I set Amat<-matrix(rbind(c(rep(0,10)),c(rep(0,10)),c(rep(0,2),1,rep(0,7)), c(rep(0,3),1,rep(0,6)),c(rep(0,10)),c(rep(0,10)), c(rep(0,6),1,rep(0,3)),c(rep(0,7),1,rep(0,2)), c(rep(0,8),1,rep(0,1)),c(rep(0,9),1,rep(0,0)),

Oops... just realized there were a couple mistakes in the question I posted regarding installation of quadprog: 1) The gcc command line is shown wrapped to the next line. Please ignore this. 2) In addition to adding a -Lc:/apps/rw1050/bin option to the command line, I also added -lRblas. Thanks, -jh- ================================= John Heumann, Agilent Technologies,

Hello to everybody, I have a quadratic programming problem that I am trying to solve by various methods. One of them is to use the quadprog package in R. When I check positive definiteness of the D matrix, I get that one of the eigenvalues is negative of order 10^(-8). All the others are positive. When I set this particular eigenvalue to 0.0 and I recheck the eigenvalues in R, the last

I upgraded to R-2.2.1 on two PPC G5 computers today. Further I want to work with the tseries package for the first time. As root with R CMD INSTALL tseries_0.10-0.tar.gz I get the following gcc-3.3 -bundle -flat_namespace -undefined suppress -L/usr/local/lib - o tseries.so arma.o bdstest.o boot.o dsumsl.o garch.o ppsum.o tsutils.o -framework vecLib -L/usr/local/lib/gcc/powerpc-apple-

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

I am having some problems using Quadprog in R. I want to minimize the objective function : 200*P1-1/2*10*P1^2+100*P2-1/2*5*P2^2+160*P3-1/2*8*P3^2+50*P4-1/2*10*P4^2+50*P 5-1/2*20*P5^2+50*P6-1/2*10*P6^2, Subject to a set of constrains including not only the variables P1, P2, P3, P4, P5, P6, but also the variables X1, X2,X3,X4,X5,X6,X7,X8,X9. As the set of variables X's are not