# Simultaneous Non-Gaussian Component Analysis

## 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