mlicaMAIN {mlica}R Documentation

Main engine function that implements the fixed point algorithm for maximum likelihood inference of ICA modes.

Description

See references for detailed description.

Usage

mlicaMAIN(prNCP, tol = 1e-04, maxit = 300, mu = 1)

Arguments

prNCP The output object of proposeNCP.
tol Tolerance level for convergence.
maxit Maximum number of iterations to allow for convergence.
mu Learning paramter for fixed point algorithm. This has already been optimised.

Value

A list with following components:

A Estimate of the mixing matrix.
B Estimate of the inverse mixing matrix.
S Estimate of the source matrix.
X Normalised data matrix.
ncp Number of independent components.
NC Binary number specifying whether best run converged,0, or not,1.
LL Log likelihood value of best run.

Author(s)

Andrew Teschendorff aet21@cam.ac.uk

References

1
Hyvaerinen A., Karhunen J., and Oja E.: Independent Component Analysis, John Wiley and Sons, New York, (2001).
2
Kreil D. and MacKay D. (2003): Reproducibility Assessment of Independent Component Analysis of Expression Ratios from DNA microarrays, Comparative and Functional Genomics 4 (3),300–317.
3
Liebermeister W. (2002): Linear Modes of gene expression determined by independent component analysis, Bioinformatics 18, no.1, 51–60.


[Package mlica version 0.6.1 Index]