similar to: Matrix Multiplication, Floating-Point, etc.

Hi. I am aware of three different R packages for linear programming: glpk, linprog, lpSolve. From what I can tell, if there are N variables and M constraints, all these solvers require the full NxM constraint matrix. Some linear solvers I know of (not in R) have a sparse matrix input format. Are there any linear solvers in R that have a sparse matrix input format? (including the

R-3.0.1 rev 62743, binary downloaded from CRAN just now; macosx 10.8.3 Hello, eigen(symmetric=TRUE) behaves strangely when given complex matrices. The following two lines define 'A', a 100x100 (real) symmetric matrix which theoretical considerations [Bochner's theorem] show to be positive definite: jj <- matrix(0,100,100) A <- exp(-0.1*(row(jj)-col(jj))^2) A's being

Hi. I have a procedure that reads a directory, loops through a set of particular .RData files, loading each one, and feeding its object(s) into a function, as follows: cvListFiles<-list.files(fnDir); for(i in grep(paste("^",pfnStub,".*\\.RData$",sep=""),cvListFiles)){ load(paste(fnDir,cvListFiles[i],sep="/")); myFunction(rliObject); rm(rliObject); };

Hi. Suppose I have a vector that I partition into disjoint, contiguous subvectors. For example, let v = c(1,4,2,6,7,5), partition it into three subvectors, v1 = v[1:3], v2 = v[4], v3 = v[5:6]. I want to find the maximum element of each subvector. In this example, max(v1) is 4, max(v2) is 6, max(v3) is 7. If I knew that the successive subvector maxima would never decrease, as in the example,

Hi. I am using R 2.3.1 on WIndows XP, and I am having trouble with the rank function in the presence of numerical NA data. I want the NA's all to get the same rank, but they don't. Here is an example from my session: >ct_align_rets_f2$liq[6851:6859] [1] 115396 NA 362595 NA 242986 340805 NA 692905 251533

Hi. I have the following code in a loop. It splits a vector into subvectors of equal size. But if the size of the original vector is not an exact multiple of the desired subvector size, then the first few subvectors have one more element than the last few. I know that the cut function could be used to determine where to break up the vector, but it doesn't seem to provide control over

Hi. I'm having trouble testing for existence of an object inside a function. Suppose I have a function: f<-function(x){ ... } and I call it with argument y: f(y) I'd like to check inside the function whether argument y exists. Is this possible, or do I have to either check outside the function or pass the name of the argument as a separate argument? If I do exists(x) or

Hi. If I have a vector, v_1, and another vector of positive integers, i_1, the same length as v_1, then rep(v_1,i_1) will repeat v_i[j] exactly i_1[j] times, like so: >rep(c(1,2,3),c(3,2,1)) [1] 1 1 1 2 2 3 > I'd like to do the same sort of thing where I replace v_1 with a matrix, and the jth row of the matrix is repeated i_1 times. Obviously, I could do this with for loops, like

Hi. I have a matrix stored in a large, tab-delimited flat file. The first row contains column names. Because the matrix is symmetric, the file has lower triangular format, so the second row contains one number, the third row two numbers, etc. In general, row k+1 contains k numbers; the matrix has 3000 rows, so the file has 3001 rows. The file has variable length records, so each row ends

Hi. You folks are so clever, I thought perhaps you could help me make another procedure more efficient. Right now I have the following setup: p is a vector of length m g is a list of length n, g[[i]] is a vector whose elements are indices of p, i.e., integers between 1 and m inclusive); the g[[i]] cover the full set 1:m, but they don't have to constitute an exact partition, theycan

Hi. Maybe this is a stupid question. If so, I apologize, but here goes. Suppose I have a function f1(x,...) that calls a function f2(y1,y2,...,yn) in the following way: if x satisfies a certain condition, then I want to call f2(x,y2,...,yn); otherwise I want to use the default value of y1, if there is one. I could do something like the following: v <- ifelse ( is.null(x), f2( , y2,...,

Hi. I am using R 2.3.1 on Windows XP. I had installed a library package into my first session and wanted the same package in my second session, so I went out to the CRAN mirror and tried to install the package, and got the following message: ********************************************************************* >utils:::menuInstallPkgs() trying URL

Hi. There was an interesting thread about a year ago, called 'Command equivalent of rgui "File, Save to File"?' (http://tolstoy.newcastle.edu.au/R/e2/help/06/09/0553.html) started by Michael Prager, and contributed to by Duncan Murdoch (I didn't notice anything beyond the four entries they posted). The question was how to replicate programmatically the "Save to

Hi. I'm checking into robust methods for principal components analysis. There seem to be several floating around. I'm currently focusing my attention on a method of Hubert, Rousseeuw, and Vanden Branden (http://wis.kuleuven.be/stat/Papers/robpca.pdf) mainly because I'm familiar with other work by Rousseeuw and Hubert in robust methodologies. Of course, I'd like to obtain

Hi. I am using R 2.5.1 on a Windows XP machine. Here is an example of a piece of code I was running in older versions of R on the same machine. I am looking for underscores and replacing them with periods. This result is from R 2.4.1: >gsub ( "\\_+","\.","AAA_I") [1] "AAA.I" > Here is what I get in R 2.5.1: >gsub (

Hi. It seems that nearly every time I try to use factanal I get the following response: >faa2db1<-factanal(mretdb1,factors=2,method="mle",control=list(nstart=25)) Error in factanal(mretdb1, factors = 2, method = "mle", control = list(nstart = 25)) : unable to optimize from these starting value(s) > In the case cited above, mretdb1 is synthetic data created

Hi. I am running regressions of several dependent variables using the same set of independent variables. The independent variable values are complete, but each dependent variable has some missing values for some observations; by default, lm(y1~x) will carry out the regressions using only the observations without missing values of y1. If I do lm(cbind(y1,y2)~x), the default will be to use

Hi. I'm looking for an R equivalent to something like function pointers in C/C++. I have a search procedure that evaluates the fitness of each point it reaches as it moves along, and decides where to move next based on its fitness evaluation. I want to be able to pass different fitness functions to this procedure. I am trying to find a good way to do this. I was thinking of passing in

Hi. I am trying to use the linear optimizer from package lpSolve in R 2.4.1 on Windows XP (Version 5.1). The problem I am trying to solve has 2843 variables (2841 integer, 2 continuous) and 8524 constraints, and I have 2 Gb of memory. After I load the input data into R, I have at most 1.5 Gb of memory available. If I start the lp with significantly less memory available (say 1 Gb), I get

Hi. I have been looking at the PCAproj function in package pcaPP (R 2.4.1) for robust principal components, and I'm trying to interpret the results. I started with a data matrix of dimensions RxC (R is the number of rows / observations, C the number of columns / variables). PCAproj returns a list of class princomp, similar to the output of the function princomp. In a case where I can