similar to: is there a way to let R do smart matrix-vector operation?

I am trying to simulate draws from a multivariate normal using mvrnorm, and am getting the following error message: Error in mu + eS$vectors %*% diag(sqrt(pmax(ev, 0)), p) %*% t(X) : non-conformable arrays I do not understand why I am getting this message, since the vector of means I am giving to the function is 13 by 1 and the variance matrix I am giving to the function is 13

is there a way to do element-by-element multiplication as in Gauss and MATLAB, as shown below? Thanks. --- a 1.0000000 2.0000000 3.0000000 x 1.0000000 2.0000000 3.0000000 2.0000000 4.0000000 6.0000000 3.0000000 6.0000000 9.0000000 a.*x 1.0000000 2.0000000 3.0000000 4.0000000

Hi, I have noticed the following: > a <- array(1:4, c(2, 2)) > A <- array(1:4, c(2,2,2)) > A + a Error in A + a : non-conformable arrays It works with a matrix + a vector, why doesn't it work with arrays? Am I missing something? How would you do the above operation efficiently (ie I need to add a matrix to each "plane" of 3-dim array)? At the moment I am using

I decided to do a direct comparison of transpose and sweep. library(microbenchmark) NN <- matrix(c(1, 2, 3, 4, 5, 6), nrow = 2, byrow = TRUE) # Example matrix lambda <- c(2, 3, 4) # Example vector colNN <- t(NN) microbenchmark( sweep = sweep(NN, 2, lambda, "/"), transpose = t(t(NN)/lambda), colNN = colNN/lambda ) Unit: nanoseconds expr min lq

So, trying to convert a very long, somewhat technical bit of lin alg MATLAB code to R. Most of it working, but raninto a stumbling block that is probaably simple enough for someone to explain. Basically, trying to 'line up' MATLAB results from an element-wise division of a matrix by a vector with R output. Here is a simplified version of the MATLAB code I'm translating: NN = [1,

Why anything but sweep? The fundamental data type in Matlab is a matrix... they don't have vectors, they have Nx1 matrices and 1xM matrices. Vectors don't have any concept of "row" vs. "column". Straight division is always elementwise with recycling as needed, and matrices are really vectors in row-major order: 1 2 3 4 5 6 is really 1 4 2 5 3 6 and when you do

> t(t(NN)/lambda) [,1] [,2] [,3] [1,] 0.5 0.6666667 0.75 [2,] 2.0 1.6666667 1.50 > R matrices are column-based. MATLAB matrices are row-based. > On Feb 27, 2024, at 14:54, Evan Cooch <evan.cooch at gmail.com> wrote: > > So, trying to convert a very long, somewhat technical bit of lin alg > MATLAB code to R. Most of it working, but raninto a stumbling block

Hi, I have this data.frame with two variables in it, > z V1 V2 1 10 8 2 NA 18 3 9 7 4 3 NA 5 NA 10 6 11 12 7 13 9 8 12 11 and a vector of means, > means <- apply(z, 2, function (col) mean(na.omit(col))) > means V1 V2 9.666667 10.714286 My intention was substracting means from z, so instictively I tried > z-means V1 V2 1 0.3333333

Hi There, While looking through the mailing list archive, I did not come across a simple minded example regarding the creation of dummy variables. The Gauss language provides the command "y = dummydn(x,v,p)" for creating dummy variables. Here: x = Nx1 vector of data to be broken up into dummy variables. v = Kx1 vector specifying the K-1 breakpoints p = positive integer in the range

Submitted for perusal, comment, improvements, and/or critique. The presentation is in 3 sections: motivation, code, and comment. Motivation: As a new-comer to R from matrix oriented Gauss and Mata, I miss the tools for using a vector (and operator) to ‘sweep’ across a matrix. Here is how these work. If M is I rows by J columns, then one entry corresponding to

Hi, this is a problem that occurs in the presence of two libraries (limma, xlsx) and leads to a crash of R. The problematic code is the wrong application of sweep or the product ("*") function on an LIMMA MAList object. To my knowledge, limma does not define a "*" method for MAList objects. If only LIMMA is loaded but not package xlsx, the code does not crash but rather

On Tue, 27 Feb 2024 13:51:25 -0800 Jeff Newmiller via R-help <r-help at r-project.org> wrote: > The fundamental data type in Matlab is a matrix... they don't have > vectors, they have Nx1 matrices and 1xM matrices. Also known as column vectors and row vectors. :) > Vectors don't have any concept of "row" vs. "column". They do in (numerical) linear

Dear all, I have a matrix with data and I want to substract from every value the previous element. Let's assume that my vector(matrix) is c<-(1,2,3,4,5) I want to get remove_previous c<-(0,1,2,3,4). How I can do that efficiently in R? I would like to thank you in advance for your help B.R Alex [[alternative HTML version deleted]]

Dear Hilmar Perhaps this gives an indication of why the infinite recursion happens: ## after calling `*` on ma and a matrix: > showMethods(classes=class(ma), includeDefs=TRUE, inherited = TRUE) Function: * (package base) e1="FOOCLASS", e2="matrix" (inherited from: e1="vector", e2="structure") (definition from function "Ops")

I want to find the DOY (Day of Year) of some dates. I think to substract the date 1. January from the data to achive this. Something like: > d <- as.Date("2006-03-13") - as.Date("2006-01-01") +1 > d Time difference of 72 days So far so good. But d is a 'difftime' object. How do I get an Integer value from that? I tried severel things, incuding the

Hi Hilmar, weird. The memory problem seems be due to recursion (my R, version 3.3.3, says: Error: evaluation nested too deeply: infinite recursion / options(expressions=)?, just write traceback() to see how it happens), but why does it segfault with xlsx? Nb xlsx is the culprit: neither rJava nor xlsxjars cause the problem. On the other hand, quick googling for r+xlsx+segfault returns tons of

I'd welcome some comments or advice regarding the situation described below. The following illustrates what seems to me to be an inconsistency in the behaviour of matrix subsetting: > Z<-matrix(c(1.1,2.1,3.1,1.2,2.2,3.2,1.3,2.3,3.3),nrow=3) > Z [,1] [,2] [,3] [1,] 1.1 1.2 1.3 [2,] 2.1 2.2 2.3 [3,] 3.1 3.2 3.3 > dim(Z) [1] 3 3 >

Hello All, I need help with my dataframe, it is big but here I am using a small table as an example. My dataframe df looks like: X1 X2 X3 1 2011-02 0.00 96.00 2 2011-02 0.00 2.11 3 2011-02 2.00 3.08 4 2011-02 0.06 2.79 5 2011-02 0.00 96.00 6 2011-02 0.00 97.00 7 2011-02 0.08 2.23 I want values in columns X2 and X3 to be checked if they are greater than

Dear all, I am having a matrix that stores data information in the following format. > roofPart1$TimeStamps[1:5,]      [,1] [,2] [,3] [,4] [,5]   [,6] [1,] 2011    7   21   15   25 20.609 [2,] 2011    7   21   15   25 23.265 [3,] 2011    7   21   15   25 26.000 [4,] 2011    7   21   15   25 28.671 [5,] 2011    7   21   15   25 31.343 I would like to be able to report some simple statistics

Dear list-members, I would like to calculate the difference between two points in time. To convert a 'time (GMT)'-character with the format "1/1/1999 01:01:01" into an object of class "POSIXct"', I first use the strptime() as suggested in the details help(as.POSIXct). e.g. starttime<-strptime("1/1/1999 01:01:01",format="%d/%m/%Y %H:%M:%S")