[R] Multidimensional scaling on a correlation matrix

Hi there, when conducting a multidimensional scaling analysis, it is possible to do this on a correlation matrix? I calculated a dissimilarity matrix by substracting the corr.matrix from 1. Then I calculated the distance matrix with d <- dist(dissimilarity matrix) and ran the isoMDS function. I

[R] Multidimensional scaling

Hi there, when conducting a multidimensional scaling analysis, it is possible to do this on a correlation matrix? I calculated a dissimilarity matrix by substracting the corr.matrix from 1. Then I calculated the distance matrix with d <- dist(dissimilarity matrix) and ran the isoMDS function. I

Re: [R] multidimensional scaling with long form data

This is my approach: If "cosa" is your data.frame . e.g. >cosa i1 i2 dis [1,] 1 1 0.00 [2,] 1 2 0.93 [3,] 1 3 0.80 [4,] 1 4 1.00 [5,] 2 2 0.00 [6,] 2 3 0.02 [7,] 2 4 0.22 [8,] 3 3 0.00 [9,] 3 4 0.95 [10,] 4 4 0.00 # first crate a square matrix of 0

[R] multidimensional scaling with long form data

I have a dissimilarity dataset with the form: 1 1 dissimilarity value 1 2 ... 1 3 1 4 2 2 2 3 2 4 ... I would like to do nonmetric multidimensional scaling with this data, but I am having trouble using this format. I would like to either find a function that accepts this format or find