similar to: means across list of data frames

Hi, I have a matrix: mymat <- matrix(runif(10*4), ncol=4) I wish to subtract the column means, down the colums, subtract the row means from the rows and add back the grand mean - all the means should be the means of mymat rather than of the new matrix. How can I do this? Any help much appreciated. Thanks Tom _________________________________________________________________

Hi all, I have a dataframe with survey data. Now I want to calculate means from several but not all columns (e.g. a1, a2, a3) and save them in a new separate column (e.g. a). Like: a = mean(a1, a2, a3) Can someone help me or give me the right key word to look for? Thanks [[alternative HTML version deleted]]

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

Hey all, I have a list of matrices. I'd like to calculate the median across all those matrices for each element. What I'd like to end up with is a matrix containing the median of all [1,1] [1,2] etc. elements across all matrices. Is there a concise way of doing that? Thanks!

Hello, Another way would be to use ?replicate and ?colMeans. set.seed(2511) # Make the results reproducible fun <- function(n){ f <- function(){ a <- runif(5, 1, 10) b <- runif(5, 10, 20) colMeans(cbind(a, b)) } replicate(n, f()) } fun(10) Hope this helps, Rui Barradas On 1/30/2018 8:58 AM, Daniel Nordlund wrote: > On 1/29/2018

On 1/29/2018 9:03 PM, smart hendsome via R-help wrote: > Hello everyone, > I have a question regarding simulating based on runif.? Let say I have generated matrix A and B based on runif. Then I find mean for each matrix A and matrix B.? I want this process to be done let say 10 times. Anyone can help me.? Actually I want make the function that I can play around with the number of simulation

I need to calculate a large number of t statistics, and would like to do so via matrix operations. So far I have figured out a way to calculate the mean of each row of the matrix: d <- matrix(runif(100000,1,10), 1000, 10) # some test data s <- rep(1,ncol(d)) # a sum vector to use for matrix multiplication means <- (d%*%s)/ncol(d) This is at least 1 order of magnitude faster than

Hello everyone, I have a question regarding simulating based on runif.? Let say I have generated matrix A and B based on runif. Then I find mean for each matrix A and matrix B.? I want this process to be done let say 10 times. Anyone can help me.? Actually I want make the function that I can play around with the number of simulation process that I want. Thanks. Eg: a <- matrix(runif(5,1, 10))

Hello , I can not get apply function to do what I want when doing stuff on rows. Let's say I want to divide the rows of matrix by their mean, the below show you get the same result weather you use 1 or 2, i.e. same result for columns than for means..:( Thanks a lot for the help, m = matrix( c(1,4,7,4,5,8,7,8,9), nrow = 3 ) divideByMean = function( v ){ return(

Dear All,   I have a matrix with 33 columns and 5000 rows. I would like to find 2 specific columns in the set: the one that holds the highest values and the one that holds the lowest values. In this case the column's mean would be apropriate to use to try to find those specific columns because each columns mean is different and they all change together based on the same "change of rate

In a newly downloaded version (today) of R-2-4-0alpha, with all packages from CRAN also installed today, I get: > library(Matrix) Erro en loadNamespace(package, c(which.lib.loc, lib.loc), keep.source = keep.source) : in 'Matrix' methods specified for export, but none defined: BIC, anova, coef, confint, deviance, fitted, fixef, formula, head, lmer, logLik, mcmcsamp, plot,

Hi All, I am illustrating a simple, two-way ANOVA using the following data and I'm having difficulty in expressing the predicted values succinctly in R. X<- data.frame(read.table(textConnection(" Machine.1 Machine.2 Machine.3 53 61 51 47 55 51 46 52 49 50

I have a list of data frames like this: a<- data.frame(x=runif(10), y = runif(10), Acc = 1) b<- data.frame(x=runif(10), y = runif(10), Acc = 0) ls<- list(a,b) and I want to remove the data frames from ls that have Acc values other than 1. How do I do that? Thanks for any help! Matthew

Hi everyone, I have dataset which I make a sample of it couple of times and each time I get the mean and standard deviation of each row for each sample. I have a function for that, which takes the name of the file and number of times to sample and then returns the mean and standard deviation for each row in each sample. Sample=function(name, n){

Hello: I'm reading in a series of text files (100 files that are each 2000 rows by 6 columns). I wish to combine the columns (6) of each file (100) and get the row mean. I'd like to end up with a data.frame of 2000 rows by 6 columns. foo <- list() for(i in 1:10){ # The real data are read in from a series of numbered text files foo[[i]] <- data.frame(x1 = rnorm(100), x2 =

Ista, et. al: efficiency? (Note: I needed to correct my previous post: do.call() is required for pmax() over the data frame) > x <- data.frame(matrix(runif(12e6), ncol=12)) > system.time(r1 <- do.call(pmax,x)) user system elapsed 0.049 0.000 0.049 > identical(r1,r2) [1] FALSE > system.time(r2 <- apply(x,1,max)) user system elapsed 2.162 0.045 2.207 ##

[text file is also attached in case you find the format of email difficult to understand] Dear useRs,You must all the planning for the christmas, but i am stucked in my office on the following issue i had a file containg information about station name, year, month, day, and discharge information. i opened it by using following command > dat1<-read.table("EL.csv",header=TRUE,

On Tue, Feb 20, 2018 at 11:58 AM, Bert Gunter <bgunter.4567 at gmail.com> wrote: > Ista, et. al: efficiency? > (Note: I needed to correct my previous post: do.call() is required for > pmax() over the data frame) > > > x <- data.frame(matrix(runif(12e6), ncol=12)) > > > system.time(r1 <- do.call(pmax,x)) > user system elapsed > 0.049 0.000

I have an array with 44800 columns and 24 rows I would like to compute the row average for the array 100 columns at a time, so I would like to end up with an array of 24 rows x 448 columns. I have tried using apply(dataset, 1, function(x) mean(x[])), but I am not sure how to get it to take the average 100 columns at a time. Any ideas would be welcomed. thanks, Spencer [[alternative HTML

Dear All, After upgrading to R-2.4.0-dapper2 (my system is ubuntu 6.06 LTS), I often met problems when loading some packages like Matrix. Here is the details: > library(Matrix) Error in loadNamespace(package, c(which.lib.loc, lib.loc), keep.source = keep.source) : in 'Matrix' methods specified for export, but none defined: Arith, Math, Math2, +, %*%, Schur, as.matrix, chol,