Title: Eigenvectors from Eigenvalues Sparse Principal Component
Maintainer: H. Robert Frost <rob.frost@dartmouth.edu>
Description: Contains logic for computing sparse principal components via the EESPCA method,
which is based on an approximation of the eigenvector/eigenvalue identity.
Includes logic to support execution of the TPower and rifle sparse PCA methods,
as well as logic to estimate the sparsity parameters used by EESPCA, TPower and rifle
via cross-validation to minimize the out-of-sample reconstruction error.

Title: Dimensionality Assessment Using Minimum Rank Factor Analysis
Description: Performs parallel analysis (Timmerman & Lorenzo-Seva, 2011
<doi:10.1037/a0023353>) and hull method (Lorenzo-Seva, Timmerman, & Kiers,
of a set of variables using minimum rank factor analysis (see ten Berge &
Kiers, 1991 <doi:10.1007/BF02294464> for more information). The package
also includes the option to compute minimum rank factor analysis by
itself, as well as the greater lower bound calculation.
Imports: stats, optimbase, psych, scales, PCovR, ggplot2, reshape2

Imports: stats, psych, scales, PCovR, ggplot2, reshape2

Title: Exploratory Factor Analysis Functions for Assessing
Description: Functions for seven different procedures for determining the number of
factors, including functions for parallel analysis and the minimum average partial
test. There are functions for conducting principal components analysis, principal
axis factor analysis, maximum likelihood factor analysis, image factor analysis,
and extension factor analysis, all of which can take raw data or correlation matrices
as input and with options for conducting the analyses using Pearson correlations,
Kendall correlations, Spearman correlations, or polychoric correlations. Varimax
rotation, promax rotation, and Procrustes rotations can be performed. Additional
functions focus on the factorability of a correlation matrix, the congruences between
factors from different datasets, and for assessing local independence.
Packaged: 2020-07-16 08:38:29 UTC; brianoconnor