vsp: Vintage Sparse PCA for Semi-Parametric Factor Analysis

Provides fast spectral estimation of latent factors in random dot product graphs using the vsp estimator. Under mild assumptions, the vsp estimator is consistent for (degree-corrected) stochastic blockmodels, (degree-corrected) mixed-membership stochastic blockmodels, and degree-corrected overlapping stochastic blockmodels.

Version: 0.1.1
Depends: R (≥ 3.1)
Imports: ggplot2, glue, invertiforms, LRMF3, magrittr, Matrix, rlang, RSpectra, stats, tibble, withr
Suggests: covr, dplyr, GGally, igraph, igraphdata, knitr, purrr, rmarkdown, scales, testthat (≥ 3.0.0), tidygraph, tidyr
Published: 2022-12-05
Author: Karl Rohe [aut], Muzhe Zeng [aut], Alex Hayes ORCID iD [aut, cre, cph], Fan Chen [aut]
Maintainer: Alex Hayes <alexpghayes at gmail.com>
BugReports: https://github.com/RoheLab/vsp/issues
License: MIT + file LICENSE
URL: https://github.com/RoheLab/vsp
NeedsCompilation: no
Materials: README NEWS
CRAN checks: vsp results


Reference manual: vsp.pdf
Vignettes: bff


Package source: vsp_0.1.1.tar.gz
Windows binaries: r-devel: vsp_0.1.1.zip, r-release: vsp_0.1.1.zip, r-oldrel: vsp_0.1.1.zip
macOS binaries: r-release (arm64): vsp_0.1.1.tgz, r-oldrel (arm64): vsp_0.1.1.tgz, r-release (x86_64): vsp_0.1.1.tgz, r-oldrel (x86_64): vsp_0.1.1.tgz
Old sources: vsp archive


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