similar to: several bugs (PR#918) lists and matrices

# Your mailer is set to "none" (default on Windows), # hence we cannot send the bug report directly from R. # Please copy the bug report (after finishing it) to # your favorite email program and send it to # # r-bugs@r-project.org # ###################################################### 1. as.numeric behaves differently in R than in S and I think this shows a bug in how S3

### I got bit again by the same bugs I wrote about a year ago. ### The bugs are related to matrices and arrays of lists. ### 1. There is a clear inconsistency in how R handles two ### functionally equivalent statements. ### array() is able to take a list and create a matrix. ### matrix() is unable to create that matrix. > vector("list", 2) [[1]] NULL [[2]] NULL >

As far as I can tell from reading The Fine Documentation (R Language Definition and Intro to R), matrices are supposed to be of homogeneous types. Yet giving matrix() an inhomogeneous list seems to work, although it produces a peculiar object: v = list(1:3,4,5,"a") m = matrix(v,nrow=2) m [,1] [,2] [1,] Integer,3 5 [2,] 4 "a" m[1,] [[1]] [1] 1 2 3 [[2]]

There is probably a simple and obvious answer to this, so sorry for wasting your time... I have a matrix of predictions from an proportional odds model (using the polr function in MASS), so the columns are the probabilities of the responses, and the rows are the data points. I have another column with the observed responses, and I want to extract the probabilities for the observed responses. As

Hi I have two arbitrarily dimensioned arrays, "a" and "b", with length(dim(a))==length(dim(b)). I want to form a sort of "corner-to-corner" version of abind(), or a multidimensional version of blockdiag(). In the case of matrices, the function is easy to write and if a=matrix(1,3,4) and b=matrix(2,2,2), then adiag(a,b) would return: [,1] [,2] [,3] [,4] [,5]

There seems to be a result type difference when subscripting a 6 x 1 matrix as compared to a 3 x 2 matrix that is caused by the ncol = 1 compared to ncol > 1. > ThinMatrix <- matrix(1:6,ncol=1) > ThinMatrix [,1] [1,] 1 [2,] 2 [3,] 3 [4,] 4 [5,] 5 [6,] 6 > FatMatrix <- matrix(1:6,ncol=2) > FatMatrix [,1] [,2] [1,] 1 4 [2,] 2 5

I have the following array: 3 dimensional object, one dimension being year. Object is 3*3*3 library(plyr, reshape) a1<-rep(c(2007,2008,2009),9) a2<-c(rep("a",9),rep("b",9),rep("c",9)) a3<-c(rep(c(rep(1,3),rep(2,3),rep(3,3)),3)) a4 <- rnorm(27) A<-data.frame(cbind(comp=a2,val=a3, year=a1, a4)) A1<-melt(A, id=c("year", "comp",

After a lot of processing I get a matrix into M. I expected each row and column to be a vector. But it is a list. R-Inferno says... "Arrays (including matrices) can be subscripted with a matrix of positive numbers. The subscripting matrix has as many columns as there are dimensions in the array—so two columns for a matrix. The result is a vector (not an array) containing the selected

How do I draw non-square matrices with image() and get the axes right? Try 1: a <- matrix(rnorm(100),20,5) image(1:20,1:5,a,asp=1,xlab="label here") # No good because the axes don't touch the image Try 2: image(1:20,1:5,a,asp=1,axes=F,xlab="label here") axis(side=1,pos=0) # No good because the x axis label is floating far from the x axis. Try 3:

I am producing 2X2 correlation matrices by a class variable. I need to extract a vector of correlation coefficients only. I am doing that in a loop (see below) but I am sure there would be a simpler way. Please help! > by(d1[,c(2,3)],d1[,1],cor) d1[, 1]: 1 c e c 1.0000000 0.1972309 e 0.1972309 1.0000000

Hi, I've been trying to figure out a special set of covariance matrices that causes some symmetric zero elements in the inverse covariance matrix but am having trouble figuring out if that is possible. Say, for example, matrix a is a 4x4 covariance matrix with equal variance and zero covariance elements, i.e. [,1] [,2] [,3] [,4] [1,] 4 0 0 0 [2,] 0 4

Hi, I'm new to programming, new to R and even new to mailing lists so please be patient with me. I need to manage many matrices generated by an R program. These matrices have different dimensions and I'd like to group them somehow. The best way would be to have a big matrix (let's call it database) where every element database[x,y] consists of a list of matrices that all have the

hello, does anyone know how I can write several matrices from R into one exel-file using different sheets for the different matrices? thank you very much in advance for your help. Marion [[alternative HTML version deleted]]

I have generated the following: x= E1 E2 E3 D1 0 0 1 D2 1 0 3 D3 0 2 0 y= E1 E2 E3 D1 0 0 1.75 D2 1.75 0 1.3125 D3 0 3.5 0 Where x and y are linked by: y =sum(x) * x / (rowSums(x)%o%colSums(x)) N=x[x[1:3,]>0] R=y[y[1:3,]>0] Now suppose I ONLY

Hi everyone: I have a kinda easy question but i do not know how to solve that in a simple way. I want to compare the rows of two matrices. col1 <- c(1,2,3,4,5,6) col2 <- c(6,5,4,3,2,1) m <- cbind(col1, col2) col3 <- c(1,3,2,6) col4 <- c(6,3,5,1) n <- cbind(col3, col4) In matrix n, for example the first row is (1,6), it is also some row

Dear Group Members, Forgive me if I am a little bit out of subject. I am looking for a good way to test the homogeneity of two variance-covariance matrices using R, prior to a Hotelling T test. Youll probably tell me that it is better to use a robust version of T, but I have no precise idea of the statistical behaviour of my variables, because they are parameters from the harmonics of

Hi every one, How is it possible to create a matrix with 3 dimensions from several 2 dimensional matrice? Is it possible that each of "elementary/building block" matrices could be called by its corresponding original name? Thanks alot. -- View this message in context:

Is there a simple way to calculate summary statistics for all the matrices or dataframes in a list? For example: > z <- list(matrix(c(2,2,2,2), ncol = 2), matrix(c(4,4,4,4), ncol = 2)) > z [[1]] [,1] [,2] [1,] 2 2 [2,] 2 2 [[2]] [,1] [,2] [1,] 4 4 [2,] 4 4 > I would like to calculate, for example, the mean value for each cell. I can do that the hard

Hello, as discussed here in more detail: https://reviews.llvm.org/D81583 the introduction of the C++20 [[no_unique_address]] attribute exposes an ABI issue on platforms that require special handling for structs/classes that are "equivalent" to a single floating-point member (or in some cases, a "homogeneous" set of floating-point members). This is because we can now for the

Hello list members I have a problem with modifying a data.frame. As an example given is a data.frame called ex : ex<-data.frame(id=c(1,2,3,4,5,6),obs=c(14,9,20,36,55,47),eff=c("A","A","B","C","C","C")) After that I would like to modify the object ex with the following short script: for (i in ex) { if(ex[i,3]=="A"||