similar to: Column-mean-values for targeted rows

I am running R 2.7.0 on a Suse 9.1 linux cluster with a job scheduler dispatching jobs and openmpi-1.0.1. I have tried running one of the examples at http://ace.acadiau.ca/math/ACMMaC/Rmpi/examples.html in Rmpi and they seem to be working, except mpi.close.Rslaves() hangs. The slaves are closed, but the master doesn't finish its script. Below is the example script and the call to R. The job is

Hi, I'm testing the efficiency of the Rmpi package regarding parallelization using a cluster. I've found and tried the task pull programming method, but even if it is described as the best method, it seems to cause deadlock, anyone could help me in using this method? here is the code I've found and tried: # Initialize MPI library("Rmpi") # Notice we just say "give us

Hi all, I am not a skillful R programmer and has I am handling with large dataframes (about 30000 x 300) I am in need of an efficient function. I have 4 dataframes with the same dimension. I need to generate other dataframe with the some dimension than the others where in each position it has the median value of the 4 values in the same position coming from the 4 dataframes. Grateful by your

Hi all, I would like to know if it is posible by, someway, to get colMeans from a data.frame with numeric as well as character data, dispersed all over the object. Note that I would like to get colMeans neglecting character data. I am really in need of some function proceeding in that way… All the best Diogo André Alagador [[alternative HTML version deleted]]

Hy all, I apologize for my ingenuity in regard to interfaces in R, but I do need it for my work. In that respect I took a simple and small example from the net (the "hello world", one) to interface R with C. I have a Windows XP OS using R.2.5.0 and in that regard I have installed the Perl and RTools files to my PC. I also wrote a proper path file, as suggested. The C program is:

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]]

I have hundreds of megabytes of price data time series, and perl scripts that extract it to tab delimited files (I have C++ programs that must analyse this data too, so I get Perl to extract it rather than have multiple connections to the DB). I can read the data into an R object without any problems. thedata = read.csv("K:\\Work\\SignalTest\\BP.csv", sep = "\t", header =

Hi all, Basically I have 2 data frames with equal dimension and I want to apply the wilcox.test to compare columns in the same position (i.e. 1st of df.A with 1st of df.B, 2nd of df.A with 2nd of df.B,...). Anyone give me an hint on this, as I think it is nicer to avoid loops, specially for huge dataframes (30000 x 200) Thanks in advance, Diogo André Alagador Portugal [[alternative HTML

Hi all, I have 2 columns in a mtrix, one of which is a column of probabilities and the other is simply a vector of integers. I want to sum all the probabilities with the same integer value and put it in a new column. For example, If my matrix is: 0.98 2 0.2 1 0.01 2 0.5 1 0.6 6 Then I should get: 0.98 2 0.99 0.2 1 0.70 0.01 2 0.99 0.5 1 0.70 0.6 6

The problem: I would like to translate the Octave algorithm in griddata.m to R. Within the griddata algorithm calls are made to the Delaunay function. For the R translation I have found delaunayn within the "geometry" package and also the deldir package. Both do similar things but give slightly different results depending on the input. The question is, what is making the results for the

Hello, On Mac OS X, certain Aqua/Quartz UI functionality requires an application to be launched from within an app bundle, or (alternatively) requires a Carbon application with a resource fork. Playing with the wxWidgets distribution, I discovered that it is quite easy and transparent to make such a Carbon app from (I guess) any command line application. When applied to the R executable called

Hello, On Mac OS X, certain Aqua/Quartz UI functionality requires an application to be launched from within an app bundle, or (alternatively) requires a Carbon application with a resource fork. Playing with the wxWidgets distribution, I discovered that it is quite easy and transparent to make such a Carbon app from (I guess) any command line application. When applied to the R executable called

Hello r-experts, I sure could us a little help. I have an ever updating text file with timestamped data in it. I can reformat in anyway I want if need be but currently I have chosen to make columns of date, time and measuresed value (comma delimeted and with the dates and times in quotes to interpret them as strings). Here is a small section of my text data file:

Hi, A simple question I hope. I wish to add a single vertical line to a plot with several density plots. Here is a simplified example. ############ thedata <- data.frame(x1=rnorm(100,1,1),x2=rnorm(100,3,1)) #create data thedata.m<-melt(thedata) densityplot(~value, thedata.m, groups=variable,auto.key=list(columns=2)) #this gives the two density plots ######### what I wish now is to add a

Thanks a lot for all of you that have reply me about opening and ending R workspaces in BATCH mode. However replies were a king general and I?m afraid I could not take the entire message from them. Therefore I chose to expose here a representative fraction of my work. I have 50 Rdata files (F1,F2,F3,F4, ,F50) with objects inside. I need to: open F1: - perform some simple operations

I need some help summarizing complex data frames (small example below): m1_1 m2_1 m3_1 m1_2 m2_2 m3_2 i1 1 1 1 2 2 2 i1 2 1 1 2 2 2 i2 2 2 1 2 2 2 For an arbitrary number of columns (say m1 ?. m199) where the column names have variable patterns, and such that each set of columns is repeated (with potentially unique data) an

Hello, # Full disclosure. I am not sure if my problem is a bug(s) in the code, or a fundamental misunderstanding on my part about what I am trying to do with these statistics. I am not familiar with maximum likelihood tests. # I currently have two vectors Aequipecten<-c(0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0,

Hi Usually "aggregate" is used to calculate things such as the sum of all data on the first day, the sum next day, and so on. But how can I calculate the mean of the first hour of all days, the mean of the second hour of all days, and so on. ??? That's Most examples: today at 1am + today at 2am + today at 3am +.... -> sum today tomorrow at 1am + tomorrow at

Dear all, I have a matrix with positive and negative values. >From this I would like to produce 2 matrices: 1st - retaining positives and putting NA in other positions 2nd - retaining negatives and putting NA in other positions and then apply rowMeans for both. I am trying to use the function ifelse in the exemplified form: ifelse(A>0,A,NA) but by putting A as a 2nd parameter it

Hi, the function outer can not apply a constant function as in the last line of the following example: > xg <- 1:4 > yg <- 1:4 > fxyg <- outer(xg, yg, function(x,y) x*y) > fconstg <- outer(xg, yg, function(x,y) 1.0) Error in outer(xg, yg, function(x, y) 1) : dims [product 16] do not match the length of object [1] Of course there are simpler ways to construct a constant