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Hi everybody, I have some problems with the function eigen. I have a square matrix and I want to calculate the eigenvalues and eigenvectors. I apply the function eigen and I get it, however when I solve the same problem in Statistica software, I realise that some eigenvectors are the opposite. How can I get the same values? Thanks in advance [[alternative HTML version deleted]]

Dear R community, I'm working with PCA and CCA methods, and I have a theoretical question. Why is it necesary to have more temporal values than variables when the CCA O PCA are going to be used? Could you advise to me some any paper about it? Thanks in advance, [[alternative HTML version deleted]]

Hello everyone, I need reshape an array. For example, if we have next array: > a <- c(1,2,3,4,5,6,7,8,9,10,11,12) > dim(a) <- c(2,2,3) > a , , 1 [,1] [,2] [1,] 1 3 [2,] 2 4 , , 2 [,1] [,2] [1,] 5 7 [2,] 6 8 , , 3 [,1] [,2] [1,] 9 11 [2,] 10 12 I need to get next matrices: 1 2 3 4 5 6 7 8 9 10 11 12 1 3 2 4 5

Dear R community, I'm a beginner with Cluster Analysis. I would like to know if there is a criterion to select the best set of clusters to do this analysis. Thanks in advance, [[alternative HTML version deleted]]

Dear R users, I would like to know if it is possible to calculate the Mean Error (ME), the Root Mean-squared error (RMSE) and absolute error (MAE) for two temporal series of directional data. Where Can I get documentation about it? Thanks in advance [[alternative HTML version deleted]]

Dear R community, I am working with huge arrays, so I spend a lot of time computing. This is my code: for (x in 1:dim(variable)[1]){ for (y in 1:dim(variable)[2]){ for (z in 1:dim(variable)[3]){ result <- max(variable[x,y,z,]) } } } Is there a more efficient procedure to do this task? Thanks in advance! [[alternative HTML version deleted]]