Dear R community: I want to simulate a regression matrix which is generated from an orthonormal matrix X of dimension 30*10 with different between-column pairwise correlation coefficients generated from uniform distribution U(-1,1). Thanks in advance! Rui [[alternative HTML version deleted]]
Spencer Graves
2003-Jul-11 21:53 UTC
[R] How to generate regression matrix with correlation matrix
What problem are you really trying to solve? The problem statement as I read it contains two logical contradictions that I see: 1. Orthonormal means X'X = Identity matrix (10 x 10). That means the pairwise correlation coefficients can NOT be different from 0. 2. Not all symmetric matrices with 1's on the diagonal and random numbers U(-1, 1) on the off diagonal are correlation matrices. Consider the following example: Cormat <- array(c(1, -0.9, -0.9, -0.9, 1, -0.9, -0.9, -0.9, 1), dim=c(3,3)) > Cormat [,1] [,2] [,3] [1,] 1.0 -0.9 -0.9 [2,] -0.9 1.0 -0.9 [3,] -0.9 -0.9 1.0 > eigen(Cormat) $values [1] 1.9 1.9 -0.8 The fact that one eigenvalue is negative means that this "Cormat" is not positive definite. hope this helps. spencer graves rui wrote:> Dear R community: > > I want to simulate a regression matrix whichis generated from an orthonormal matrix X of dimension 30*10 with different between-column pairwise correlation coefficients generated from uniform distribution U(-1,1).> > Thanks in advance! > > Rui > [[alternative HTML version deleted]] > > ______________________________________________ > R-help at stat.math.ethz.ch mailing list > https://www.stat.math.ethz.ch/mailman/listinfo/r-help
Maybe Matching Threads
- Generate multivariate normal data with a random correlation matrix
- More clear statement about the question of how to generate regression matrix with correlation matrix
- Inverse matrix using eigendecomposition
- how do I make a correlation matrix positive definite?
- speeding up a pairwise correlation calculation