| FG {JADE} | R Documentation |
Joint Diagonalization of Real Positive-definite Matrices
Description
This is a slightly modified version of Flury's FG algorithm for the joint diagonalization of k positive-definite matrices. The underlying function is written in C.
Usage
FG(X, weight = NULL, init = NULL, maxiter = 100, eps = 1e-06, na.action = na.fail)
Arguments
X |
A matrix of k stacked pxp matrices with dimension c(kp,p) or an array with dimension c(p,p,k). |
weight |
A vector of length k to give weight to the different matrices, if NULL, all matrices have equal weight. |
init |
Initial value for the orthogonal matrix to be estimated, if NULL, the identity matrix is used. |
maxiter |
Maximum number of iterations. |
eps |
Convergence tolerance. |
na.action |
A function which indicates what should happen when the data contain 'NA's. Default is to fail. |
Value
A list with the components
V |
An orthogonal matrix. |
D |
A stacked matrix with the diagonal matrices or an array with the diagonal matrices. The form of the output depends on the form of the input. |
iter |
The Fortran function returns also the number of iterations. |
Author(s)
Jari Miettinen
References
Flury, B. D. (1998), Common principal components and related models, Wiley, New York.