search for: 100x50

Hello, 1. After I generate a 100x50 matrix by x3<-matrix(0,100,50);for (i in 1:100) {x1<-rpois(50, mu[i]);x2<-x1; x2[runif(50)<.01]<-0; x3[i,]<-x2}, 2. I want to calculate means and sample variances of each row and create a new matrix 100x2; 3. I then want to repeat above procedure 500 times so that eventually I w...

...I've got clusters and would like to match individual records to each cluster based on a sum of squares deviation. For each cluster and individual, I've got 50 variables to use (measured in the same way). Matrix 1 is individuals and is 25000x50. Matrix 2 is the cluster centroids and is 100x50. The same variables are found in each matrix in the same order. I'd like to calculate the 'distance' of matrix 1 to matrix 2 and get a ranking of matrix 2's distances (and row IDs 1 to 100) sorted by distance. I tried using the RDIST and DIST functions but they have true (Euclid...

This is a fairly entry level question - so any guidance on this would be appreciated... I have two sets of residuals, one of 100 values (A), and one of 10,000 values (B). There are 50 paired sets of these values. The data is in the form of two matrices (100x50 and 10,000x50). The goal is to correlate the residuals from A and B, to identify a those B values that go up when a single A value goes up, and so on. Is there a specific package that is well set up for this? Thanks for your help. -- View this message in context: http://r.789695.n4.nabble.com...

...heatmap of the bicluster results. With the code given in the biclust package I can only get the heatmap for one cluster at a time (drawHeatmap function). Is there any way that I can get the heatmap for all the clusters at the same time? The code that I am using (biclust documentation) is: #Random 100x50 matrix with a single, up-regulated 10x10 bicluster s2=matrix(rnorm(5000),100,50) s2[11:20,11:20]=rnorm(100,3,0.3) # cluster 1 s2[31:40,31:40]=rnorm(100,5,0.7) # cluster 2 set.seed(1) bics <- biclust(s2,BCPlaid(), back.fit = 2, shuffle = 3, fit.model = ~m + a...

I have a matrix of values... for exemple the matrix could be 100 rows and 50 columns... I would like to resample the matrix to obtain a new matrix -> a 10x5 matrix So i need to calculate a new value for every cell, i would like to use a weightened mean to do this. I explain this thing better: In the exemple the original matrix would be divided into 50 partial-matrix, for every partial-matrix