similar to: New package: gRain - gRAphical Independence Networks

I am new to using S4 methods and have run into this problem (on Windows XP using R 2.4.1): I am writing a package in which I use the graph package. I define my own classes of graphs as: setOldClass("graphsh") setOldClass("ugsh") setIs("ugsh", "graphsh") (I know that I "should have" used setClass instead - and I will eventually - but right now

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 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

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

Hi, I installed R-3.1.1 on AIX-5.3 and my installation hanged up while installing Matrix Package. so i killed the gmake ; gmake install the software nad tired installing Matrix package manually - [ncmr0202][/gpfs1/home/shivali/gang/R-3.1.1/bin/package]> /gpfs1/home/shivali/gang/R-3.1.1/bin/R CMD INSTALL Matrix the package compiled successfully but while loading Matrix package the

Hi All, I've hit a problem using nls. I think it may be a restriction in the applicability of nls and I may have found a fix, but I've been wrong before. This example is simplified to the essentials. My real application is much more complicated. Take a function of matrix 'x' with additional arguments: matrix 'aMat' whose values are _not_ to be determined by nls vector

Hi I'm having problems getting the "factorized" argument in solve.QP (part of the quadprog library) to work as expected. The helpfile states that when the factorized argument is set to TRUE, then the function requires the inverse of a square-root factor of the Hessian instead of the Hessian itself. That is, when factorized=TRUE, the Dmat argument should be a matrix R^(-1), such

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

Hi All, I have the following adjacency matrix for a directed graph: [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [1,] 0 0 0 0 0 0 0 0 [2,] 0 0 0 0 0 0 0 0 [3,] 1 0 0 0 0 0 0 0 [4,] 0 0 1 0 0 0 0 0 [5,] 0 0 1 0 0 0 0 0 [6,] 1 1 0 0 0 0 0 0 [7,] 0 0

The package 'graph' defines classes graph and graphNEL (extending graph) and a union,graph,graph-method. These are all exported and fully documented. The package 'GSEABase' Imports: graph and importClassesFrom(graph, graphNEL). GSEABase defines methods on union for its own classes (not graph / graphNEL), and has exportMethods(union). union,graph,graph-method is not used in

Dear all, I need to maximize the v: v= D' W D D is a column vector ( n , 1) W is a given matrix (n, n) subject to: sum D= 1 (BTW, n is less than 300) I´ve tried to use maxBFGS, as follows: ##################################### objectiveFunction<-function(x) { return(t(D)%*%W%*%D) } Amat<-diag(nrow(D)) Amat<-rbind((rep(-1, nrow(D))), Amat) bvec<-matrix( c(0), nrow(D)+1,

Hello everyone, Im working with graphNEL object and want to extract all the nodes which have adjacent nodes with at least 20 nodes in between them. acc(graph, graphnodes) obviously provides a list for the accessable nodes of every node from a node and a number of the edges between them. Like this: $`hsa:8379` hsa:100131844 hsa:10393 hsa:246184 hsa:29882 hsa:29945 1

Deal R Users, I'm trying to find out how can I compute probabilities on a Bayesian Network using R. The Bayesian Network I modelled is shown at http://www.dsr.inpe.br/~mello/1727/BNgrapmodel.png and I'd like to know how can I proceed (commands on R) to answer questions like: (1) what is the probability of S=T given C=T, L=T, R=F, H=F and D=F; or (2) what is the probability of S=T

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've been using the package "graph" in the BioConductor assortment and writing some functions based on its classes. My question is not specific to this package or BioConductor (I think), but it serves as a useful example. I recently wanted to look at the code for the function "edgeMatrix" for the class "graphNEL". Usually I would type > func.foo and

Can somebody save-me? Thanks in advance! #R script: #trying to find out how solve a discrete Bayesian Belief Network. #option: using 'catnet' package #BEGIN library(catnet) cnet <- cnNew(nodes = c("a", "b", "c"), cats = list(c("1", "2"), c("1", "2"), c("1", "2")), parents = list(NULL, c(1), c(1,

Hi hi i have a problem trying to connect to the mysql database when I do a rake it says: Access denied for user: ''@localhost'' to database '''' My database.yml file is fine Any ideas why this is happening -- Posted via http://www.ruby-forum.com/.

Hi list: This is my first time to post my question on the list. Thanks for your help. I am solving a quadratic programming using R. Here is my question: w = arg min 0.5*w'Mw - w'N s. t. sum(w) = 1; w>0 note: w is weight vector, each w_i must >=0, and the sum of w =1. Here is my R code: A <-matrix(c(2.26,1.26,1.12,1.12,2.27,1.13,1.12,1.13,2.2),3,3); B <-

Ian, this one is special just for you. I''m sending it as an attachment because my email client will mangle it. This patch will remove the cmake dependency from xen prior to autoconf stubdom This patch applies ontop of [VTPM v7 3/8] vtpm/vtpmmgr and required libs to stubdom/Makefile You can apply it to your tree by doing the following: git rebase -i <VTPM v7 3/8 revision>

I'm trying to teach myself about Bayesian Networks and am working with the following data and the bnlearn package. I understand the conceptual aspects of BNs, but I'm not sure how to specify the response variables in R when constructing a dag plot. I've cecked ?hc and done numerous google searches without luck. Can anyone help? library("bnlearn")