Description Usage Arguments Value Author(s) Examples
Decomposes a matrix into sparse eigenevectors to maximize explained variance.
1 | networkEiganat( Xin, sparam = c(0.1, 0.1), k = 5, its = 100, gradparam = 1, mask = NA, v, prior, pgradparam = 0.01)
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inmatrix |
n by p input images , subjects or time points by row , spatial variable lies along columns |
inmask |
optional antsImage mask |
other params |
see sccan for other parameters |
outputs a decomposition of a population or time series matrix
Avants BB
1 2 3 4 5 | ## Not run:
mat<-replicate(100, rnorm(20))
mydecom<-networkEiganat( mat )
## End(Not run)
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