Simultaneous Non-Gaussian Component Analysis

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Documentation for package ‘singR’ version 0.1.2

• DESCRIPTION file.
• User guides, package vignettes and other documentation.

Help Pages

%^%	Calculate the power of a square matrix
angleMatchICA	Match the colums of Mx and My
aveM	Average Mj for Mx and My Here subjects are by rows, columns correspond to components
calculateJB	Calculates the sum of the JB scores across all components, useful for determining rho.
covwhitener	Returns square root of the precision matrix for whitening
create.graph.long	create graph dataset with netmat and mmp_order a data.frame called with vectorization of reordered netmat by mmp_order.
curvilinear	Curvilinear algorithm with r0 joint components
curvilinear_c	Curvilinear algorithm based on C code with r0 joint components
est.M.ols	Estimate mixing matrix from estimates of components
exampledata	Data for simulation example 1
gen.inits	Generate initialization from specific space
greedymatch	Greedy Match
lngca	Decompose the original data through LNGCA method.
matchICA	match ICA
NG_number	find the number of non-Gaussian components in the data.
orthogonalize	Orthogonalization of matrix
permmatRank_joint	Permutation test to get joint components ranks
permTestJointRank	Permutation test with Greedymatch
pmse	Permutation invariant mean squared error
signchange	Sign change for S matrix to image
singR	SImultaneous Non-Gaussian Component analysis for data integration.
standard	Standardization with double centered and column scaling
theta2W	Convert angle vector into orthodox matrix
tiltedgaussian	tiltedgaussian
vec2net	Create network matrices from vectorized lower diagonals 'vec2net' transfer the matrix vectorized lower diagonals into net to show the component image.
whitener	Whitening Function