ncchung/jaws: Jackstraw Weighted Shrinkage Methods

Estimate sparse loadings (i.e., coefficients) of Principal Component Analysis, Logistic Factor Analysis, and other techniques in the context of Latent Variable Models. Generally, this can facilitate calculation of shrunken R^2 and related quantities that represent estimated latent variables more accurately. Using systematic variation driven by latent variables, this package also estimate covariance matrices of high-dimensional data when a number of rows (variables) is exceedingly larger than a number of observations (columns).

Getting started

Package details

AuthorNeo Christopher Chung <[email protected]>, John D. Storey <[email protected]>
MaintainerNeo Christopher Chung <[email protected]>
Package repositoryView on GitHub
Installation Install the latest version of this package by entering the following in R:
ncchung/jaws documentation built on May 23, 2019, 1:05 p.m.