similar to: Median across matrices

I have a list of data frames like the following: set.seed(123) a<- data.frame(x=runif(10), y = runif(10), sample = seq(1,10)) b<- data.frame(x=runif(10), y = runif(10), sample = seq(1,10)) L<- list(a,b) All data frames in the list have the same dimensions. I need to calculate the sample means for x and y. The real data are lists of several thousand quite large dataframes, so I need

I have an application where I have a function to calculate results for a 2-way table or matrix, which returns a matrix with one less row and column. To keep this short, the function below captures the structure: fun2way <- function(f){ if (!length(dim(f)) ==2) stop("only for 2-way arrays") R <- dim(f)[1] C <- dim(f)[2] f[1:(R-1), 1:(C-1)] } Now, I want to

Hi. I have 2 tables, with same dimensions (8000 x 5). Something like: tab1: V1 V2 V3 V4 V5 14.23 1.71 2.43 15.6 127 13.20 1.78 2.14 11.2 100 13.16 2.36 2.67 18.6 101 14.37 1.95 2.50 16.8 113 13.24 2.59 2.87 21.0 118 tab2: V1 V2 V3 V4 V5 1.23 1.1 2.3 1.6 17 1.20 1.8 2.4 1.2 10 1.16 2.6 2.7 1.6 11 1.37 1.5 2.0 1.8 13 1.24 2.9 2.7 2.0 18 I need generate a table of averages, the

. HI there, I'd like to show demonstrate how the chi-squared distribution works, so I've come up with a sample data frame of two categorical variables y<-data.frame(gender=sample(c('Male', 'Female'), size=100000, replace=TRUE, c(0.5, 0.5)), tea=sample(c('Yes', 'No'), size=100000, replace=TRUE, c(0.5, 0.5))) And I'd like to create a list of 100

### 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 >

Is there no better way to merge one array into another than iterating over the array you wish to append with each() and push()ing the elements on to the other array? Here''s what I mean: var arr1 = [1, 2, 3, 4, 5]; var arr2 = [''a'', ''b'', ''c'']; $A(arr2).each(function(el) { arr1.push(el) }); Is there no better way to do it than this?

Hey all, I'm performing polynomial regression. I'm simulating x values using runif() and y values using a deterministic function of x and rnorm(). When I perform polynomial regression like this: fit_poly <- lm(y ~ poly(x,11,raw = TRUE)) I get some NA coefficients. I think this is due to the high correlation between say x and x^2 if x is distributed uniformly on the unit interval

i'm somehow embarrassed to even ask this, but is there any built-in method for doing this: my_list <- list() my_list[[1]] <- matrix(1:20, ncol = 5) my_list[[2]] <- matrix(20:1, ncol = 5) now, knowing that these matrices are identical in dimension, i'd like to unfold the list to a 2x4x5 (or some other permutation of the dim sizes) array. i know i can initialize the array, then

Hi, Is there a way in llvm IR to emit multiple data elements within a single compilation unit that a) are guaranteed to appear sequentially in the final binary (in the order they appear in the llvm IR), and b) will be removed on an individual basis by the optimizers and/or linker in case they are not referenced from anywhere ? Defining them as "appending" puts them all into a

Hi, Suppose I have these two matrices (could be more). What I need to do is to store these matrices into a hash. So that I can call back any of the matrix back later. Is there a way to do it? > mat_1 [,1] [,2] [1,] 9.327924e-01 0.067207616 [2,] 9.869321e-01 0.013067929 [3,] 9.892814e-01 0.010718579 [4,] 9.931603e-01 0.006839735 [5,] 9.149056e-01 0.085094444

Dear R-users, My goal is to construct a levelplot (from the lattice package) with 4 or more individual plots sharing the same colorkey. While this appears to be relatively simple using functions, I haven't been able to find a solution using data matrices. An example of a working levelplot with just one matrix: d <- replicate(10,rnorm(10)) levelplot(d) I have found partial solutions using

Dear All, I've an array with some missing values (NA) in between. I want to remove that particular matrix if a missing value is detected. How can I do so? Thank you very much. Best regards, Ray [[alternative HTML version deleted]]

Hi folks, I'm trying to do something that seems like it should easy, but it apparently isn't. I have two large matrices, both containing a number of missing values at different cells. I would like to average these matrices, but the NAs are preventing me. I get a "non-numeric argument to binary operator" error. That's the first problem.

Hi R, I have a list of matrices. I need to get the sum of all the matrices in the list. Example: a=b=c=d=matrix(1:4,2,2) l=list(a,b,c,d) I need: > a+b+c+d [,1] [,2] [1,] 4 12 [2,] 8 16 Something like do.call("+",l) is not working...why is this? I may not be knowing the number of matrices in the list... Thanks, Shubha This e-mail

Given a variable aa in the workspace, some of its attributes are: > typeof(aa) [1] "list" > mode(aa) [1] "list" > length(aa) [1] 2 How do I retrieve the maximum indices, in this case 2,3,4? The variable itself is: > aa [[1]] [[1]][[1]] [[1]][[1]][[1]] [1] 37531.52 [[1]][[1]][[2]] [1] 62787.32 [[1]][[1]][[3]] [1] 5503.184 [[1]][[1]][[4]] [1] 33832.8

Oh, this seemed so simple (and I'm sure the answer will be, as usual, so thanks in advance for enlightening me). I need to sort each row of a matrix independent of the others. For example, > test <- matrix(c(8,7,1,2,6,5,9,4,3),nrow=3) > test [,1] [,2] [,3] [1,] 8 2 9 [2,] 7 6 4 [3,] 1 5 3 I can get each row sorted well enough. > sort(test[1,]) [1]

Hi everyone, Speed is the key here. I need to find the difference between a vector and its one-period lag (i.e. the difference between each value and the subsequent one in the vector). Let's say the vector contains 10 million random integers between 0 and 1,000. The solution vector will have 9,999,999 values, since their is no lag for the 1st observation. In R we have: #Set up input vector

Hello Chandler, > ``` > void f(int *arr1, int *arr2, int length) { > intptr_t rel_offset = arr2 - arr1; > int *arr1_end = arr1 + length; > for (int *p = arr1; p < arr1_end; p += sizeof(int)) { > do_something(p, p + rel_offset); > } > } > ``` > > For example, a common loop optimization technique is something like the following in *pseudocode* (note

Hi, xtabs() creates a table of counts. I want a table of proportions -- that is, I want to divide every vector (along a particular dimension) by its sum. The tiny example below does that. The call to xtabs() creates a matrix "A" with dimensions ("x1","x2","y"). I transform "A" using aperm() and aaply() to get the matrix "B". The

you can pull it with jQuery via javascript for example evry 10 seconds, and update the informations you want, at least its the way i do it. Am 23.11.2023 um 00:13 schrieb Thomas Jensen: > Thank you, Ben! > > I was afraid it would be very complicated to get the information > extracted, but it was very simple. My only problem now is to find a way > to update the text on the