Man pages for bbuchsbaum/neuroca
neuroca: multiblock component analysis for neuroimaging data

badaBarycentric Discriminant Analysis
block_applyblock_apply apply a function to each block of a multi-block...
block_index_listblock_index_list
block_lengthsblock_lengths
block_matrixblock_matrix
block_matrix_listblock_matrix_list
block_pcablock_pca
block_projector#' projector_list projector_list <- function(Xs)...
boot_ratiocompute bootstrap ratios for a list of matrices
boot_sdcompute standard deviations for a set of bootstrap results
bootstrapbootstrap a model
collapseColumn-wise average a matrix of variables, collapsing over...
contributionscontributions
cross_validatecross_validate a model
fast_estim_ncompfast_estim_ncomp
genpcaGeneralized Principal Components Analysis
get_blockget_block
group_meansgroup_means
hpcahclust_pca
loadingsloadings
mfamultiple factor analysis
muascamuasca
mubadaMultiple Subjects Barycentric Discriminant Analysis
nblocksnblocks extract the number of blocks in a mutli-block data...
ncompncomp get the number of components in the estimated model
neurocaneuroca - multiblock component analysis methods for...
nneg_pcanneg_pca
partial_scorespartial_scores
proc_rotprocrustes rotation
projectproject
project_colsproject_cols
projection_funprojection_fun
project_tableproject_table
pseudo_svdpseudo_svd
reconstructreconstruct the data with some number of components
reproducibilityreproducibility
resampleresample data from a model fit
residualizeCompute a regression model for each column in a matrix and...
residualsget the residuals of a model, after removing the first...
rotateapply a rotation matrix to a solution
scadascada
scorepredGiven a set of projected scores and a set of reference...
scoresscores
shrink_pcashrink_pca
svd_wrappersvd_wrapper
bbuchsbaum/neuroca documentation built on Oct. 13, 2018, 1:43 p.m.