Vintage Sparse PCA for Semi-Parametric Factor Analysis

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Documentation for package ‘vsp’ version 0.1.1

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

Help Pages

bff	Find features most associated with cluster membership
bind_svd_u	Add Z factor loadings to node table of tidygraph
bind_svd_v	Add Z factor loadings to node table of tidygraph
bind_varimax_y	Add Z factor loadings to node table of tidygraph
bind_varimax_z	Add Z factor loadings to node table of tidygraph
get_svd_u	Get left singular vectors in a tibble
get_svd_v	Get left singular vectors in a tibble
get_varimax_y	Get left singular vectors in a tibble
get_varimax_z	Get left singular vectors in a tibble
get_y_hubs	Get most important hubs for each Z factor
get_z_hubs	Get most important hubs for each Z factor
plot_ipr_pairs	Plot pairs of inverse participation ratios for singular vectors
plot_mixing_matrix	Plot the mixing matrix B
plot_svd_u	Create a pairs plot of select Y factors
plot_svd_v	Create a pairs plot of select Y factors
plot_varimax_y_pairs	Create a pairs plot of select Y factors
plot_varimax_z_pairs	Create a pairs plot of select Y factors
screeplot.vsp_fa	Create a screeplot from a factor analysis object
set_y_factor_names	Give the dimensions of Z factors informative names
set_z_factor_names	Give the dimensions of Z factors informative names
vsp	Semi-Parametric Factor Analysis via Vintage Sparse PCA
vsp.default	Semi-Parametric Factor Analysis via Vintage Sparse PCA
vsp.dgCMatrix	Semi-Parametric Factor Analysis via Vintage Sparse PCA
vsp.igraph	Semi-Parametric Factor Analysis via Vintage Sparse PCA
vsp.Matrix	Semi-Parametric Factor Analysis via Vintage Sparse PCA
vsp.matrix	Semi-Parametric Factor Analysis via Vintage Sparse PCA
vsp.svd_like	Perform varimax rotation on a low rank matrix factorization
vsp_fa	Create a vintage sparse factor analysis object