| rMAP {fungible} | R Documentation |
Generate Correlation Matrices with Specified Eigenvalues
Description
rMAP uses the method of alternating projections (MAP) to generate correlation matrices with specified eigenvalues.
Usage
rMAP(eigenval, eps = 1e-12, maxits = 5000, Seed = NULL)
Arguments
eigenval |
A vector of eigenvalues that must sum to the order of the desired correlation matrix. A fatal error will occur if sum(eigenval) != length(eigenval). |
eps |
Convergence criterion. Default = 1e-12. |
maxits |
Maximm number of iterations of MAP. |
Seed |
Either a user supplied seed for the random number generator or ‘NULL’ for a function generated seed. Default Seed = ‘NULL’. |
Value
R |
A correlation matrix with the desired spectrum. |
evals |
Eigenvalues of the returned matrix, R. |
convergence |
(Logical) TRUE if MAP converged to a feasible solution, otherwise FALSE. |
Author(s)
Niels Waller
References
Waller, N. G. (2016). Generating correlation matrices with specified eigenvalues using the method of alternating projections.
Examples
## Example
## Generate a correlation matrix with user-specified eigenvalues
R <- rMAP(c(2.5, 1, 1, .3, .2), Seed = 123)$R
print(R, 2)
# [,1] [,2] [,3] [,4] [,5]
#[1,] 1.000 0.5355 -0.746 -0.0688 -0.545
#[2,] 0.535 1.0000 -0.671 -0.0016 -0.056
#[3,] -0.746 -0.6711 1.000 0.0608 0.298
#[4,] -0.069 -0.0016 0.061 1.0000 0.002
#[5,] -0.545 -0.0564 0.298 0.0020 1.000
eigen(R)$values
#[1] 2.5 1.0 1.0 0.3 0.2