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WeightedPCA: PCA for heterogeneous quality samples

Version Stable Dev Project Status: WIP – Initial development is in progress, but there has not yet been a stable, usable release suitable for the public. PkgEval Build Status Coverage

👋 This package provides research code and work is ongoing. If you are interested in using it in your own research, I'd love to hear from you and collaborate! Feel free to write: [email protected]

Please cite the following paper for this technique:

David Hong, Fan Yang, Jeffrey A. Fessler, Laura Balzano. "Optimally Weighted PCA for High-Dimensional Heteroscedastic Data", SIAM Journal on Mathematics of Data Science 5:222-250, 2023. https://doi.org/10.1137/22M1470244 https://arxiv.org/abs/1810.12862

In BibTeX form:

@Article{hyfb2023owp,
  title =        "Optimally Weighted {PCA} for High-Dimensional Heteroscedastic Data",
  author =       "David Hong and Fan Yang and Jeffrey A. Fessler and Laura Balzano",
  journal =      "{SIAM} Journal on Mathematics of Data Science",
  year =         "2023",
  volume =       "5",
  number =       "1",
  pages =        "222--250",
  DOI =          "10.1137/22M1470244",
}