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  "Title": "Tools for Principal Component Analysis-Based Data Structure\nComparisons",
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  "Authors@R": "c(person(\"Anne Helby\", \"Petersen\", , email=\"ahpe@sund.ku.dk\", role=c(\"aut\", \"cre\")),\nperson(\"Bo\", \"Markussen\", , email=\"bomar@math.ku.dk\", role=c(\"aut\")))",
  "Description": "A suite of non-parametric, visual tools for assessing\ndifferences in data structures for two datasets that contain\ndifferent observations of the same variables. These tools are\nall based on Principal Component Analysis (PCA) and thus\neffectively address differences in the structures of the\ncovariance matrices of the two datasets. The PCADSC tools\nconsist of easy-to-use, intuitive plots that each focus on\ndifferent aspects of the PCA decompositions. The cumulative\neigenvalue (CE) plot describes differences in the variance\ncomponents (eigenvalues) of the deconstructed covariance\nmatrices. The angle plot presents the information loss when\nmoving from the PCA decomposition of one dataset to the PCA\ndecomposition of the other. The chroma plot describes the\nloading patterns of the two datasets, thereby presenting the\nrelative weighting and importance of the variables from the\noriginal dataset.",
  "License": "GPL-2",
  "Encoding": "UTF-8",
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  "URL": "https://github.com/annennenne/PCADSC",
  "BugReports": "https://github.com/annennenne/PCADSC/issues",
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  "Repository": "https://annennenne.r-universe.dev",
  "Date/Publication": "2025-05-21 07:39:53 UTC",
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  "Maintainer": "Anne Helby Petersen <ahpe@sund.ku.dk>",
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