similar to: superposing lattice plots

Hello my friends, here is a code I wrote with no loops on matrix that is taking too long (2 seconds and I call him 720 times --> 12 minutes): mat1 and mat2 are both matrix with 103 columns and 164 rows. sequence <- matrix(seq(1 : ncol(mat1))) returns <- apply(sequence, 1, function, mat1= mat1, mat2 = mat2, day = 1) function<- function(mat1, mat2, colNb, day){

Hello...i want to find the empirical rate for type 1 error using fixed trimmed mean. To make it easy, i'm referring to journal given by this website http://www.academicjournals.org/ajmcsr/PDF/pdf2011/Yusof%20et%20al.pdf. I already run the programme and there is no error in it but i got zero for the empirical rate of type 1 error. The empirical rate for the type 1 error given in the journal

I guess this has a simple solution: I have matrix 'mat1' which has row and column names, e.g.: A B C row1 0 0 0 row2 0 0 0 .... rown 0 0 0 I have a another matrix 'mat2', essentially a subset of 'mat1' where the rownames are all in 'mat1' e.g.: B row3 5 row8 6 row54 7 I want to insert the values of matrix mat2 for column B (in reality it could be some or

Hello, I haven't found errors in your code. I implemented the test in the paper (the first, fixed symetric mean) and it also gives me zero Type I errors, when alpha = 0.05. Try to see the value of min(pv) or to plot the histogram of 'pv', hist(pv) and you'll see that there are no significant p-values, at that level. Anyway I'll continue to look at it, but my first

Dear List, I often have to merge two or more data frames containing unique row names but with some columns (names) common to the two data frames and some columns not common. This toy example will explain the kind of setup I am talking about: mat1 <- as.data.frame(matrix(rnorm(20), nrow = 5)) mat2 <- as.data.frame(matrix(rnorm(20), nrow = 4)) rownames(mat1) <- paste("site",

I'm calculating correlations between two matrices mat1 <- matrix(sample(1:500,25), ncol = 5, dimnames=list(paste("mat1row", 1:5, sep=""), paste("mat1col", 1:5, sep=""))) mat2 <- matrix(sample(501:1000,25), ncol = 5, dimnames=list(paste("mat2row", 1:5, sep=""), paste("mat2col", 1:5, sep="")))

Sorry for the verbose example. I want to row bind two matrices, and all works except I want the column labelled "row" to be sequential in the new matrix, shown as "mat3" here, i.e. needs to be 1:6 and not 1:3 repeated twice. Any suggestions? Thanks J > colnm1 <- c("row","ti","counti") > colnm2 <-

Hi, Suppose that I have a list where each component is a list of two matrices. I also have a vector of weights. How can I collapse my list of lists into a single list of two matrices where each matrix in the result is the weighted sum of the corresponding matrices. I could use a loop but this is a nested calculation so I was hoping there is a more efficient way to do this. To help clarify,

Hi. I'm looking for an efficient way of writing a function(x,mat1,mat2). n<-4 m<-4 r<-3 x <- array(sample(1:1000)/10^4,rep.int(n,m)) mat1 <- matrix(sample(1:1000)/10^4,n,n) mat2 <- matrix(sample(1:1000)/10^4,n,n) It needs to work for *any* itegers n, r<=m with output (in horrible gory detail) equivalent to: ans<-array(0,rep.int(n,(m+1))) for(i1 in 1:n) for(i2 in

Hello R-Experts, I am a beginner to R. Can someone please look at my problem I am trying to append the files in R but couldn't get the answer properly. My code is mat1<-matrix(0,2,3) mat2<-matrix(1,2,3) write.table(mat1,"foo.csv",sep=",",col.names=NA) write.table(mat2,"foo.csv", sep=",", col.names=NA, append = TRUE) I am getting a warning

Hello, I have a matrix mat1 of dim [1,8] and mat2 of dim[30,8], I want to replace the first row of mat2 with mat1, this is what I do: mat2[1,]<-mat1 but it transforms mat2 in a list I don't understand, I want it to stay a matrix... ----- Anna Lippel -- View this message in context: http://n4.nabble.com/Simple-question-on-replace-a-matrix-row-tp1427857p1427857.html Sent from the R help

Hi, I went ahead and implemented something. However: - I cannot garantie it gives correct results since, unfortunately, the data used in Syrjala 1996 is not published along with the paper. To avoid mistakes, I started by coding things in a fast and simple way and then tried to optimize the code. At least all versions given the same results. - As expected, the test is still quite slow

Dear R heleprs   Suppose I have following data   Scenarios combination_names     series1    series2 Sc1 MAT2 GAU1 7.26554 8.409778 Sc2 MAT2 GAU2 7.438128 8.130275 Sc3 MAT3 GAU1 8.058422 8.06457 Sc4 MAT1 GAU2 8.179855 8.022071 Sc5 MAT3 GAU2 8.184033 8.191831 Sc6 MAT3 GAU2 7.50312 8.232425 Sc7 MAT1 GAU2 7.603291 8.200993 Sc8 MAT1 GAU1 8.221755 8.380097 Sc9 MAT3 GAU2 7.904908

Dear all, Ket say I have 3 matrices : mat1 <- matrix(rnorm(16), 4) mat2 <- matrix(rnorm(16), 4) mat3 <- matrix(rnorm(16), 4) Now I want to merge those three matrices to a single one with dimension 4*3=12 and 4 wherein on resulting matrix, row 1,4,7,10 will be row-1,2,3,4 of "mat1", row 2,5,8,11 will be row-1,2,3,4 of "mat2" and row 3,6,8,12 will be row-1,2,3,4 of

Hi, How to turn a character string into an unevaluated R object? I want to load some files in a directory into data matrix R objects. I could do this with read.table and assign (see below). Then, I want to turn the character string representing a file name (the evaluated expression of i) into an unevaluated R object. Basically, I want to create matrices whose names are the same as the related file

Hello fellow R users, I have a matrix computation that I imagine should be relatively easy to do, however I cannot figure out a nice way to do it. I have two matrices, for example mat1 <- matrix(c(1:5,rep(NA,5), 6:10), nrow=3, byrow=T) mat2 <- matrix(c(2:6, 6:10, rep(NA,5)), nrow=3, byrow=T) I'd like to compute the element-wise average for non-NA entries. Of course (mat1+mat2)/2

Hi everyone, I'm trying to calculate correlation coefficients between corresponding columns in two matrices with identical dimensions but different data. The problem is that the matrices contain NAs in different locations. I am using the following code to try to calculate correlations between complete sets of data: #Code start maxcol<-ncol(mat1) for (i in 1:maxcol) {

Hi, Not sure if this is what you wanted: ?mat1<- as.matrix(read.table(text=" ????? 33??????? 45??? 50 ????? NA?????? NA?? 54 ",sep="",header=FALSE)) mat2<- as.matrix(read.table(text=" 24??????????????? 0.0000000??????? 0.0000000 0.0000000??????? 14??????????????? 0.0000000 0.0000000 0.0000000??????? 10 ",sep="",header=FALSE)) ?mat1%*%mat2 ?# ??? V1?

Hi, I had a large file for which I require a subset of rows. Instead of reading it all into memory, I use the awk command to get the relevant rows. However, I'm doing it pretty inefficiently as I write the subset to disk, before reading it into R. Is there a way that I can read it into an R object without writing to disk? For example, this is what I do currently: ## write test sample file

Dear all, I am using "coxme" function in Kinship library to fit random treatment effect nested within centre. I got 3 treatments (0,1,2) and 3 centres. I used following commands, but got an error. > ugroup=paste(rep(1:3,each=3),rep(0:2,3),sep='/') > mat1=bdsmatrix(rep(c(1,1,1,1,1,1,1,1,1),3),blocksize=rep(3,3),dimnames=list(ugroup,ugroup)) >