Simultaneous Non-Gaussian Component Analysis

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Documentation for package ‘singR’ version 0.1.1

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%^% 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