similar to: zero-extent matrices (PR#958)

Prof Brian Ripley <ripley@stats.ox.ac.uk> writes: > "[<-.zoffset" <- function(x, i, j, value) > { > if(!missing(i) && is.numeric(i)) i <- i+1 > if(!missing(j) && is.numeric(j)) j <- j+1 > NextMethod("[<-") > } > works in S but not in R. (Which I think is a bug.) I next tried Yup, there's a bug in there

Is there a good reason not to allow matrix extents to be zero? I have been writing a function which fits glms under certain linear constraints. I fit the model with a reduced set of variables and then transform back to the original set. This involves operating on submatrices of the covariance matrix and subsets of the coefficients. Sometimes these subsets are empty. A zero-length subset of the

The help for cbind() and rbind() says "For cbind (rbind), vectors of zero length (including NULL) are ignored unless the result would have zero rows (columns), for S compatibility. (Zero-extent matrices do not occur in S3 and are not ignored in R.)" This leads to an inconsistency. M <- matrix(NA, 0, 0) # Make a 0x0 matrix N <- matrix(NA, 0, 1) # Make a 0x1 matrix

I'm wanting to perform analysis (e.g. using eigen()) of binary matrices - i.e. matrices comprising 0s and 1s. For example: n<-1000 test.mat<-matrix(round(runif(n^2)),n,n) eigen(test.mat,only.values=T) Is there a more efficient way of setting up test.mat, as each cell only requires a binary digit? I imagine R is setting up a structure which could contain n^2 floats. Thanks in advance

Dear all, I am finding difficulty in the following, I would like to create an empty matrix e.g. 10x10 of 0s and sequentially fill this matrix with randomly placed a 1s until it is saturated. Producing 100 matrices of sequentially increasing density., This process needs to be randomized 1000 times., I assume i should run this along the following lines, 1) Create 1000 matrices all zeros, 2) add

m1 <- matrix(rnorm(40), ncol=4) m2 <- matrix(rnorm(40), ncol=4) I would like to subtract first column of m1 from all columns of m2, subtract 2nd of m1 from all columns of m2, and so on. Obviously, I am not using the appropriate function outer(m1, m1, "-"), since the first column isn't all 0s. _________________________________________________________________

I've been scratching my head over this one for too long. I'm hoping someone out there can solve this riddle. I have two vectors of characters, v1 and v2, both of length L, and two matrices of logicals, m1 and m2, both of dimension N*L. The first matrix of logicals corresponds to the first vector of characters, and the second to the second. The matrices are telling me which of the

Hi all, I'm new to R, so needless to say I have a couple questions (which I hope I haven't missed through the documentation). I have several files in lower triangular matrix form. For each of these matrices, I want to perform some form of hierarchical clustering on each matrix and capture the output of the clustering. The first problem I run into is actually loading the matrix file

> Date: Sat, 8 Jun 2024 19:16:22 -0400 > From: Ben Bolker <bbolker at gmail.com> > > The ASAN errors occur *even if the zero-length object is not actually > accessed*/is used in a perfectly correct manner, i.e. it's perfectly > legal in base R to define `m <- numeric(0)` or `m <- matrix(nrow = 0, > ncol = 0)`, whereas doing the

Has anyone written subscripting methods for matrices which are indexed from zero? i.e. functions such as "[.zoffset" and "[<-.zoffset" which would allow, given an appropriate function "zmatrix" "zmatrix" <- function(...) { robj <- matrix(...) class(robj) <- "zoffset" robj } fred <- zmatrix(1:20, 4, 5) fred[0, 4] # would be 17

Full_Name: Raymond Salvador Version: R 1.6.2 OS: Windows ME Submission from: (NULL) (131.111.93.195) The mean function applied on individual components of several correlation matrices gives a wrong result (gives the first value instead of the mean). Here there is a simple example x1 <- rnorm(10,1,1) y1 <- rnorm(10,1,1) z1 <- cbind(x1,y1) w1 <- cor(z1) x2 <- rnorm(10,1,1) y2

Hi, According to the help file for model.frame/get_all_vars, the following should produce the same output from both functions, but it doesn't... > dat <- list(X=matrix(1:15,5,3),z=26:30) > model.frame(~z+X,dat) z X.1 X.2 X.3 1 26 1 6 11 2 27 2 7 12 3 28 3 8 13 4 29 4 9 14 5 30 5 10 15 > get_all_vars(~z+X,dat) [1] z X <NA> <NA> <0

Hi, there was a change concerning logical operations about a year ago: https://github.com/wch/r-source/commit/9e19d3e3dd5f657b5cfefe562bdd7ede2e2b8786 It's related to a discussion on this list: https://hypatia.math.ethz.ch/pipermail/r-devel/2016-September/073068.html <https://hypatia.math.ethz.ch/pipermail/r-devel/2016-September/073068.html> A change in logic.c:134 influences the

Not a bug in a very strict sense, but still something to be fixed eventually: > s <- sapply(0:7, function(i) rawShift(charToRaw("my text"),i)) > s ... nothing is printed at all > str(s) raw [1:7, 1:8] 6d 79 20 74 ... > c(s) [1] 6d 79 20 74 65 78 74 da f2 40 e8 ca f0 e8 b4 e4 80 d0 94 e0 d0 68 c8 00 a0 [26] 28 c0 a0 d0 90 00 40 50 80 40 a0 20 00 80 a0 00 80 40 40 00

Anyone for a little debugging? > matrix(numeric(0),0,0) Floating point exception (core dumped) [I've decided to make a habit of sending bugs that I'm not going to attack right away to R-devel, in case someone might be interested in chipping in and saving the core team the work] -- O__ ---- Peter Dalgaard Blegdamsvej 3 c/ /'_ --- Dept. of Biostatistics

>From one of my students' simulations: m <- matrix(1, 0, 0) # 1 to force numeric not logical eigen(m) and segfault in TRED2 in src/appl/eigen.f Easy to fix, but I wonder what else might have been overlooked? (svd is protected). --please do not edit the information below-- Version: platform = sparc-sun-solaris2.7 arch = sparc os = solaris2.7 system = sparc, solaris2.7 status =

A matrix or array with one of its dimensions having zero elements looses its dimension after multiplying with scalar. Admittedly this is an extreme case, however it DOES make sense to retain an objects formal structure after multiplying with a scalar, as e.g. a matrix with zero rows IS a legal object in S. BTW, the prototype does retain the dimension. Best Jens Oehlschlägel # replication code

After fixing princomp(), recently, {tiny negative eigen-values are possible for non-negative definite matrices} Fritz Leisch drew my attention to the fact the not only eigen() can be funny, but also svd(). Adrian Trappleti found that the singular values returned can be "-0" instead of "0". This will be a problem in something like sd <- svd(Mat) $ d

Full_Name: Julien Gagneur Version: 2.2.1 OS: Linux (Suse 9.3) Submission from: (NULL) (194.94.44.4) Using the SparseM library (SparseM_0.66) and the e1071 library (e1071_1.5-12) I fail using svm method with a sparse matrix. Here is a sample example. I experienced the same problem under Windows. > library(SparseM) [1] "SparseM library loaded" > library("e1071")

A change to R-devel (SVN r86629 or https://github.com/r-devel/r-svn/commit/92c1d5de23c93576f55062e26d446feface07250 has changed the handling of pointers to zero-length objects, leading to ASAN issues with a number of Rcpp-based packages (the commit message reads, in part, "Also define STRICT_TYPECHECK when compiling inlined.c.") I'm interested in discussion from the