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Available fitting methods include conjugate gradient\nalgorithms, a coordinate descent Majorization-Minimization (MM)\nalgorithm, and a block coordinate descent algorithm based on\ndata projection that supports matrices with missing values and\nallows new individuals to be projected as supplementary rows\nwithout refitting the model. A cross-validation procedure is\nprovided to select the number of latent dimensions k.\nReferences: Babativa-Marquez and Vicente-Villardon (2021)\n; Vicente-Villardon and Galindo (2006,\nISBN:9780470973196).", "License": "MIT + file LICENSE", "Encoding": "UTF-8", "LazyData": "true", "RoxygenNote": "7.3.3", "URL": "https://github.com/jgbabativam/BiplotML", "BugReports": "https://github.com/jgbabativam/BiplotML/issues", "NeedsCompilation": "no", "Packaged": { "Date": "2026-05-08 19:17:04 UTC", "User": "root" }, "Author": "Jose Giovany Babativa-Marquez [cre, aut] (ORCID:\n)", "Maintainer": "Jose Giovany Babativa-Marquez ", "Repository": "https://cran.r-universe.dev", "Date/Publication": "2026-05-08 17:47:37 UTC", "RemoteUrl": "https://github.com/cran/BiplotML", "RemoteRef": "HEAD", "RemoteSha": "e7124c6c078d3600a1a1bfd358da44055b4edfe4", "MD5sum": "f9e8d9893a8e5e245bd3b0fce31f52bb", "_user": "cran", "_type": "src", "_file": "BiplotML_1.1.1.tar.gz", "_fileid": 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