Package: PCADSC
Type: Package
Title: Tools for Principal Component Analysis-Based Data Structure
        Comparisons
Version: 0.8.0
Authors@R: c(person("Anne H.", "Petersen", , email="ahpe@sund.ku.dk", role=c("aut", "cre")),
             person("Bo", "Markussen", , email="bomar@math.ku.dk", role=c("aut")))
Description: A suite of non-parametric, visual tools for assessing differences in data structures
    for two datasets that contain different observations of the same variables. These tools are all 
    based on Principal Component Analysis (PCA) and thus effectively address differences in the structures
    of the covariance matrices of the two datasets. The PCASDC tools consist of easy-to-use, 
    intuitive plots that each focus on different aspects of the PCA decompositions. The cumulative eigenvalue
    (CE) plot describes differences in the variance components (eigenvalues) of the deconstructed covariance matrices. The
    angle plot presents the information loss when moving from the PCA decomposition of one dataset to the 
    PCA decomposition of the other. The chroma plot describes the loading patterns of the two datasets, thereby
    presenting the relative weighting and importance of the variables from the original dataset. 
Depends: R (>= 3.2.2)
License: GPL-2
Encoding: UTF-8
LazyData: true
Imports: reshape2, methods, pander, ggplot2, Matrix
RoxygenNote: 5.0.1
URL: https://github.com/annepetersen1/PCADSC
BugReports: https://github.com/annepetersen1/PCADSC/issues
NeedsCompilation: no
Packaged: 2017-04-19 10:00:23 UTC; zms499
Author: Anne H. Petersen [aut, cre],
  Bo Markussen [aut]
Maintainer: Anne H. Petersen <ahpe@sund.ku.dk>
Repository: CRAN
Date/Publication: 2017-04-19 10:07:43 UTC
Built: R 4.6.0; ; 2026-04-26 09:20:11 UTC; unix
