similar to: selecting vector elements using matrices and combining the results

I have been looking for a way to write R-generated reports to Microsoft Word documents. In the past, I used the package R2wd, but for some reason I haven't been able to get it to work on my current set up. R version 2.15.0 (64-bit) Windows 7 Enterprise - Service Pack 1 Microsoft Office Professional Plus 2010 - Word version 14.0.6123.5001 (32-bit) I gave the package

I?m confused by the difference in the fit of a gam model (in package mgcv) when I specify an interaction in different ways. I would appreciate it if someone could explain the cause of these differences. For example: x <- c(105, 124, 124, 124, 144, 144, 150, 176, 178, 178, 206, 206, 212, 215, 215, 227, 229, 229, 229, 234, 234, 254, 254, 290, 290, 303, 334, 334, 334, 344,

Hi, I've tried to look through all the previous related Threads/posts but can't find a solution to what's probably a simple question. ? I have a data frame comprised of three columns e.g.: ? ID1?ID2?Value a?b?1 b?d?1 c?a?2 c?e?1 d?a?1 e?d?2 ? I'd like to convert the data to a matrix i.e.: ? ?a b c d e a n/a 1 2 1 n/a b 1 n/a n/a 1 n/a? c 2 n/a n/a n/a 1 d 1 1 n/a n/a 2 e n/a n/a 1

I have run into a speed issue, and given the size of the problem it feels like there should be an easy solution. Here is the problem statement with some arbitrary numbers added. #p,q: vector with length(q)==length(p)==10000 and length(levels(p))==3000 #y,z: vectors with length(levels(y))=length(y)==length(z)==5000 for (i in levels(p)){ q[i==p]<-z[i==y]} At first i used two for loops which

Hi all, I have 6 datasets(dataframes Assem_ContigsLen7 through all_ContigsLen12) containing 3 columns (contig_id, contig_length, read_count). Each dataset is composed of 3 types of contigs (assemblies of genomic fragments), 1- all Bacterial fragments, 2 - all Viral fragments, 3 - mixed fragments. I identified the type of contig through a merge with another table with just contig_id and

Hi, I have a dataframe column from which I want to calculate the number of 1's in each entry. Some column values could, for example, be "0001001000" and "11110000111". To get the number of occurrences from a string I use this: sum(unlist(strsplit(mydata[,"my_column"], "")) == "1") However, as my data is not in string form.. How do I convert

I want to overlay a small inset map on top of another map, but I can't figure out how to do it. For example, here are two different maps: # map 1 - Ohio map("state", region= "ohio") # map 2 - US with Ohio darkened map("state") map("state", region="ohio", fill=T, add=T) I would like to add map 2 as a small inset in the corner of map 1. I

R Users, Abstracts are now being accepted for the ASA Conference on Statistical Practice February 15-17, 2017 Portland, Oregon USA The deadline for submission is Thursday June 22. Presentations will be 35 minutes long and fall into four broad themes: Communication, Collaboration, and Career Development Data Modeling and Analysis Data Science and Big Data

Hello I have 4 1000*1000 matrix A,B,C,D. I want to use the corresponding element of the 4 matrices. Using the "for loop" as follow: E<-o for (i in 1:1000) {for (j in 1:1000) { E<-fisher.test(matrix(c(A[i][j],B[i][j],C[i][j],D[i][j]),2))#call fisher.test for every element } } It is so time-consuming Need vectorization Yours sincerely ZhaoXing Department of

Hi, For example, given two 2x2 matrices m1 and m2. I would like to add/subtract element by element > m1 [,1] [,2] [1,] NA NA [2,] 1 2 > m2 [,1] [,2] [1,] 1 NA [2,] NA 2 > m1 + m2 [,1] [,2] [1,] NA NA [2,] NA 4 How can I ignore the NA, and get this ? Hope the solution can be extended to subtract and modulo also. [,1] [,2]

My two matrices are roughly the sizes of m1 and m2. I tried using two apply and cor.test to compute the correlation p.values. More than an hour, and the codes are still running. Please help to make it more efficient. m1 <- matrix(rnorm(100000), ncol=100) m2 <- matrix(rnorm(10000000), ncol=100) cor.pvalues <- apply(m1, 1, function(x) { apply(m2, 1, function(y) { cor.test(x,y)$p.value

Dear R-helpers, I have a huge data-set so need to avoid for loops as much as possible. Can someone think how I can compute the result in the following example (that uses a for-loop) using some version of apply instead (or any other similarly super-efficient function)? example: #Suppose a matrix: m1=cbind(1:5,1:5,1:5) #The aim is to create a new matrix with every column containing the

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. _________________________________________________________________

Dear Members, I have two estimated transition matrices and I want to compare them. In fact I want to check the hypothesis if they come from the same process. I tried to look for some test but all I found was independence test of contingency tables. The following code shows that the usual chi-squared test statistic does not follow chisq distribution. MCRepl <- 5000 khi12 <- rep(0,MCRepl)

I would like to be able to randomise presence-absence (i.e. binary) matrices whilst keeping both the row and column totals constant. Is there a function in R that would allow me to do this? I'm working with vegetation presence-absence matrices based on field observations. The matrices are formatted to have sites as rows and species as columns. The presence of a species on a site is

Dear All, I have two matrices A (40 x 732) and B (40 x 1230) and would like to calculate correlation between them.  I can use: cor(A,B, method="pearson") to calculate correlation between all possible pairs. But the issue is that there is one-many specific mappings between A and B and I just need to calculate correlations for those pairs (not all). Some variables in A (proteins, say p1)

I'm looking for a good form in which to store matrix results of a simulation. I am doing a simulation study. Each simulation generates some data and then analyzes it. I want to record the results of many simulations and analyze them. Say r has the results of one simulation, and I care about r$coefficients, a vector of coefficients, and r$var, the estimated covariance matrix. I'll do

Dear all, I have 3 matrices with the same dimension, A,B,C and I would like to produce a matrix D where in each position would retrieve the max(or min) value along A,B,C taken from the same position. I guess that apply functions should fit, but for matrices objects I am not getting it. thanks in advance, Diogo André Alagador [[alternative HTML version deleted]]

Dear R users, I want to check matrices when i change the order of the rows or/and the order of the columns or/and the combination of them i will give an example what i want  1  -1  1  1      1  1   1  1 -1  -1 -1 -1    -1 -1  -1  -1   1  1    1  1     1 -1    1   1 these 2 matrices are identical because i change the first row and make it third   1  -1  1  1      -1  1   1  1 -1  -1 -1

A list contains several matrices. Over all matrices (list elements) I'd like to access one matrix cell: m <- matrix(1:9, nrow=3, dimnames=list(LETTERS[1:3], letters[1:3])) l <- list(m1=m, m2=m*2, m3=m*3) l[[3]] # works l[[3]][1:2, ] # works l[[1:3]][1, 1] # does not work How can I slice all C-c combinations in the list? S?ren -- S?ren Vogel, Dipl.-Psych. (Univ.), PhD-Student, Eawag,