Description Usage Arguments Details Value Author(s) References See Also Examples
The Amari distance is a measure between two nonsingular matrices. Useful for checking for convergence in ICA algorithms, and for comparing solutions.
1 |
V |
first matrix |
W |
second matrix |
orth |
are the matrices orthogonal; default is |
Formula is given in second reference below, page 570.
a numeric distance metween 0 and 1
Trevor Hastie
Bach, F. and Jordan, M. (2002). Kernel independent component analysis,
Journal of Machine Learning Research 3: 1-48
Hastie, T., Tibshirani, R. and Friedman, J. (2009) Elements of
Statistical Learning (2nd edition), Springer.
http://www-stat.stanford.edu/~hastie/Papers/ESLII.pdf
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 | dist="n"
N=1024
p=2
A0<-mixmat(p)
s<-scale(cbind(rjordan(dist,N),rjordan(dist,N)))
x <- s %*% A0
###Whiten the data
x <- scale(x, TRUE, FALSE)
sx <- svd(x) ### orthogonalization function
x <- sqrt(N) * sx$u
target <- solve(A0)
target <- diag(sx$d) %*% t(sx$v) %*% target/sqrt(N)
W0 <- matrix(rnorm(2*2), 2, 2)
W0 <- ICAorthW(W0)
W1 <- ProDenICA(x, W0=W0,trace=TRUE,Gfunc=G1)$W
fit=ProDenICA(x, W0=W0,Gfunc=GPois,trace=TRUE, density=TRUE)
W2 <- fit$W
#distance of FastICA from target
amari(W1,target)
#distance of ProDenICA from target
amari(W2,target)
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