vsp.svd_like: Perform varimax rotation on a low rank matrix factorization

In RoheLab/vsp: Vintage Sparse PCA for Semi-Parametric Factor Analysis

Perform varimax rotation on a low rank matrix factorization

Description

Perform varimax rotation on a low rank matrix factorization

Usage

## S3 method for class 'svd_like'
vsp(
  x,
  rank,
  ...,
  centerer = NULL,
  scaler = NULL,
  recenter = FALSE,
  renormalize = FALSE,
  kaiser_normalize_u = FALSE,
  kaiser_normalize_v = FALSE,
  rownames = NULL,
  colnames = NULL,
  match_columns = TRUE
)

Arguments

x	Either a graph adjacency matrix, igraph::igraph or tidygraph::tbl_graph. If x is a matrix or Matrix::Matrix then x[i, j] should correspond to the edge going from node i to node j.
rank	The number of factors to calculate.
...	These dots are for future extensions and must be empty.
centerer	TODO
scaler	TODO
recenter	Should the varimax factors be re-centered around the original factor means? Only used when center = TRUE, defaults to FALSE.
renormalize	Should the regularized graph laplacian be used instead of the raw adjacency matrix? Defaults to TRUE. If center = TRUE, A will first be centered and then normalized.
kaiser_normalize_u	Whether or not to use Kaiser normalization when rotating the left singular vectors U. Defaults to FALSE.
kaiser_normalize_v	Whether or not to use Kaiser normalization when rotating the right singular vectors V. Defaults to FALSE.
rownames	Character vector of row names of x. These row names are propagated into the row names of the U and Z. Defaults to NULL.
colnames	Character vector of column names of x. These column names are propagated into the row names of the V and Y. Defaults to NULL.
match_columns	Should the columns of Y be re-ordered such that Y[, i] corresponds to Z[, i] to the extent possible? Defaults to TRUE. Typically helps with interpretation, and often makes B more diagonally dominant.

Examples

library(LRMF3)
library(RSpectra)

s <- svds(ml100k, k = 2)
mf <- as_svd_like(s)
fa <- vsp(mf, rank = 2)

RoheLab/vsp documentation built on Nov. 6, 2024, 10:08 p.m.