search for: dvec

...an itself. That is, when factorized=TRUE, the Dmat argument should be a matrix R^(-1), such that the Hessian of the objective function is t(R) %*% R. I modified the example in the helpfile slightly to test this out: R = matrix(rnorm(9),3,3) R.inv = solve(R) Dmat = t(R) %*% R dvec = c(0,5,0) Amat = matrix(c(-4,-3,0,2,1,0,0,-2,1),3,3) bvec = c(-8,2,0) x1 = solve.QP(Dmat=Dmat, dvec=dvec, Amat=Amat, bvec=bvec, factorized=FALSE) x2 = solve.QP(Dmat=R.inv, dvec=dvec, Amat=Amat, bvec=bvec, factorized=TRUE) print(x1$solution) print(x2$solution) I wou...

...t <= 1 I understand the general principle of creating box constraints by creating pairs of positive and negative values within the constraint matrix ( http://tolstoy.newcastle.edu.au/R/help/05/10/14251.html), but when I pass this expanded constraint matrix to solve.QP it complains that Amat and dvec are incompatible. How should I expand dvec (and consequently Dmat) to accomodate the larger Amat? Moreover, I am unclear how to apply the meq equality constraint across more than one cell (i.e. rows summing to one) although I have attempted a guess below. Any help warmly received. Selwyn. #######...

...<= w #<=1=bUp] to Amat <- rbind(-1, 1, -mu, mu) dim(bLo) <- c(n,1) dim(bUp) <- c(n,1) bvec <- rbind(-1, 1, mu.target, Inf, bLo, -bUp) zMat <- matrix(rep(0,2*n*n),ncol=n, nrow=n*2) zMat[,1] <- c(rep(1,n), rep(-1,n)) Amat <- t(rbind(Amat, zMat)) #So I set Dmat=Cov and set dvec=0 Dmat=Cov dvec=rep(0, nrow(Amat)) #The first two rows of Amat should be equality constraints (so weights sum to 1) meq <- 2 sol <- solve.QP(Dmat=Dmat, dvec=dvec, Amat=Amat, bvec=bvec, meq) sol

...lted return of the investor I've done the following code but it doesn't make what I want it to do. The weights aren't all positive and the \mu isn't reached. What's wrong with my code? Require(quadprog) Dmat<-diag(1,7,7) # muss als quadratische Matrix eingegeben werden Dmat dvec<-matrix(0,7,1) # muss als Spaltenvektor eingegeben werden dvec mu<-0 # (in Mio. €) bvec<-c(1,mu,matrix(0,7,1)) # muss als Spaltenvektor eingegeben werden bvec mu_r<-c(19.7,33.0,0.0,49.7, 82.5, 39.0,11.8) Amat<-matrix(c(matrix(1,1,7),7*mu_r,diag(1,7,7)),9,7,byrow=T) # muss als Matri...

...ot; calculated by solve.QP I would be very happy, if anyone could help and tell me, where's my mistake. Thank you very much. Fabian My R-code also containing the sampel of quadprog starts here: #sample from quadprog package library(quadprog) Dmat <- matrix(0,3,3) diag(Dmat) <- 1 dvec <- c(0,5,0) Amat <- matrix(c(-4,-3,0,2,1,0,0,-2,1),3,3) bvec <- c(-8,2,0) erg<-solve.QP(Dmat,dvec,Amat,bvec=bvec) print(erg) erg<-erg$solution -dvec%*%erg+.5*erg^T%*%Dmat%*%erg # my "non working" sample n<-2 k<-2 Dmatj<-diag((n-1),n) Dmatj[l...

Dear All, I attempted to fit a DVEC and a BEKK multivariate GARCH model, but am wondering which package to use. 1. I tried to use "rmgarch" package in R, but I couldn't find the subroutines for DVEC and BEKK. 2. I tried to find "rmgarch" package of R, which is not located on the official R site. This is...

...*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 affecting the objective function, I assume that I have to enter them as zero's in the vector "dvec" and the matrix "Dmat". My program states as: mat<-matrix(0,15,15) diag(Dmat)<-c(10,5,8,10,20,10,0,0,0,0,0,0,0,0,0) dvec<- c(-200,-100,-160,-50,-50,-50,0,0,0,0,0,0,0,0,0) Amat<- matrix(c(-1,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,-1,0,1, 0,0,0,0,0,0,0...

...mple using Python+rpy which works (well, except for some R error I haven't figured out yet) in the old installation: import numpy import rpy rpy.r("library(quadprog)") Dmat = numpy.identity(3, numpy.float_) print Dmat rpy.r.assign("Dmat", Dmat) dvec = numpy.array([0,5,0], numpy.float_) print dvec rpy.r.assign("dvec", dvec) Amat = numpy.array([[-4,-3,0], [2,1,0], [0,-2,1]], numpy.float_) print Amat rpy.r.assign("Amat", Amat.transpose()) bvec = numpy.array([-8,2,0], numpy.float_) print bvec r...

...matrix. Are there any (fast) packages that allows me to do QP with (large) semidefinite matrices? Example: t <- 100 y <- signalConvNoisy[1,] D <- crossprod(H,H) d <- crossprod(H,y) A <- cbind(rep(-1, nrow(H)), diag(ncol(H))) b0 <- c(t, rep(0, ncol(H))) sol <- solve.QP(Dmat=D, dvec = d, Amat = A, bvec = b0)$solution Error in solve.QP(Dmat = D, dvec = d, Amat = A, bvec = b0) : matrix D in quadratic function is not positive definite! Thanks in advance, Andreas Jensen

I got following error while I was using solve.QP() in my problem: > Dmat = matrix(c(0.0001741, 0.0001280, 0.0001280, 0.0002570), nrow=2) > dvec = t(c(0,0)) > Amat = matrix(c(-1,1,0,-1,0, 1,0,1,0,-1), nrow=5) > bvec = c(-20000, 1, 1, -50000, -50000) > solve.QP(Dmat,dvec,Amat,bvec=bvec) Error in solve.QP(Dmat, dvec, Amat, bvec = bvec) : Amat and dvec are incompatible! > Can anyone tell me where is the error in my defin...

...subject to setTargetRisk(myspec)=0.08 using only constraints="LongOnly" I can run feasiblePortfolio() using a spec file that specifies the weights, and it works fine. When I run maxreturnPortfolio(mydata,myspec,"LongOnly"), however, I get Error in .rquadprog(Dmat = args$Dmat, dvec = args$dvec, Amat = args$Amat, : NA/NaN/Inf in foreign function call (arg 8) Troubleshooting, it appears to be occurring in the routine eqsumWConstraints within .rquadprogArguments. Specifically, when that routine calls ceq <- c(Return = targetReturn, Budget = -1) it produces > ceq Retu...

...to implement hundreds of constraints just solve.QP that I am unaware of ? Thanks for any suggestions. # IN THE CODE BELOW, WE MINIMIZE # -3*b1 + 4*b2 + 6*b3 # SUBJECT TO # b1 + b2 + b3 >=0 # -(b1 b2 + b3) >= 0 # IE : b1 + b2 + b3 = 0. Dmat <- matrix(0,3,3) # QUADRATIC TERM dvec <- c(-3,4,6) # LINEAR TERM Amat <- matrix(c(1,-1,0,1,-1,0,1,-1,0),3,3) #print(Amat) bvec = c(0,0,0) # THIRD ZERO IS SAME AS NO CONSTRAINT result <- solve.QP(Dmat, dvec, Amat)

...6" "2018-04-13" "2018-04-20" "2018-05-18" [8] "2018-06-15" "2018-08-17" "2018-09-21" "2018-10-19" "2018-11-16" "2019-01-18" "2019-06-21" [15] "2020-01-17" "2020-06-19" R> dvec <- anydate(names(aapl_total)) # helper variable R> ind <- dvec >= anydate("2018-04-01") & dvec <= anydate("2018-04-30") # one example R> ind [1] FALSE FALSE FALSE TRUE TRUE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE R...

...ckage, http://www.R-project.org<http://www.r-project.org/> % Copyright 1995-2007 R Core Development Team % Distributed under GPL 2 or later \name{QR.Auxiliaries} \title{Reconstruct the Q, R, or X Matrices from a QR Object} \usage{ qr.X(qr, complete = FALSE, ncol =) qr.Q(qr, complete = FALSE, Dvec =) qr.R(qr, complete = FALSE) } \alias{qr.X} \alias{qr.Q} \alias{qr.R} \arguments{ \item{qr}{object representing a QR decomposition. This will typically have come from a previous call to \code{\link{qr}} or \code{\link{lsfit}}.} \item{complete}{logical expression of length 1. Indicates wh...

Hi Dirk, Thanks for your note. I understand that expiry dates are the dates that the option expires, so I don't think that I am confused about that (although the upper limits of one's confusion is difficult to accurately estimate). My lack of clarity come from treating those "dates" as actual dates as opposed to strings, which one could reasonably interpret them to be from

...he efficientPortfolio function even though I'm setting the target return to the mean of the TargetReturn I obtain from the portfolio object created by the feasiblePortfolio function. First Error: Error: targetReturn >= min(mu) is not TRUE Second Error: Error in .rquadprog(Dmat = args$Dmat, dvec = args$dvec, Amat = args$Amat, : NA/NaN/Inf in foreign function call (arg 8) I'm using a timeSeries created from daily stock prices of selected stocks on the Bombay Sensex. My timeSeries is of the following format date stock1 stock2 stock3 I don't understand why I'm getting these...

...s) #now all eigenvalues are positive: D.values.new <- eigen(D.vectors%*%D.quad%*%ginv(D.vectors),only.values=F)$values D.values.new [1] 4.609489e+04 2.458166e+03 8.232288e+01 1.961199e+00 5.976441e-01 [6] 2.810968e-01 1.253140e-09 1.428534e-12 Dmat <- D.vectors%*%D.quad%*%ginv(D.vectors) dvec <- -c(-2910.533769,-2905.609008,-3012.223863,-16274.97455,-17222.46423,-18380.6 391,-357.8878464,-379.6371849) #this ensures that coefficients are positive: Amat <- matrix(0,8,8) diag(Amat) <- 1 bvec <- rep(0,8) #it says D is not positive definite ... solve.QP(Dmat,dvec,Amat,bvec=...

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 multiplication, i.e. Amat'*x, not using the matrix-product, i.e. Amat'%*%x, required for the sums on the left-hand-side of 1-6). I would very much appreciate a suggestion on this problem. Thank you,...

Hi there, I have a major problem (major for me that is) with solve.QP and I'm new at this. You see, to solve my quadratic program I need to have the lagrange multipliers after each iteration. Solve.QP gives me the solution, the unconstrained solution aswell as the optimal value. Does anybody have an idea for how I could extract the multipliers? Thanx, Serge "Beatus qui prodest quibus

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