{ "_id": "6a49ec1054b1f994258aad2c", "Package": "paran", "Version": "1.5.5", "Date": "2026-02-12", "Title": "Horn's Test of Principal Components/Factors", "Authors@R": "c(person(given = \"Alexis\", family =\"Dinno\", role = c(\"aut\", \"cre\", \"cph\"), email = \"alexis.dinno@pdx.edu\", comment = c(ORCID = \"0000-0003-2560-310X\")))", "Description": "An implementation of Horn's technique for numerically and\ngraphically evaluating the components or factors retained in a\nprinciple components analysis (PCA) or common factor analysis\n(FA). Horn's method contrasts eigenvalues produced through a\nPCA or FA on a number of random data sets of uncorrelated\nvariables with the same number of variables and observations as\nthe experimental or observational data set to produce\neigenvalues for components or factors that are adjusted for the\nsample error-induced inflation. Components with adjusted\neigenvalues greater than one are retained. paran may also be\nused to conduct parallel analysis following Glorfeld's (1995)\nsuggestions to reduce the likelihood of over-retention.", "URL": "https://alexisdinno.com/Software/index.shtml#paran,\nhttps://alexisdinno.com/Software/files/PA_for_PCA_vs_FA.pdf", "License": "GPL-2", "LazyLoad": "true", "Encoding": "UTF-8", "NeedsCompilation": "no", "Packaged": { "Date": "2026-06-13 06:35:23 UTC", "User": "root" }, "Author": "Alexis Dinno [aut, cre, cph] (ORCID:\n)", "Maintainer": "Alexis Dinno ", "Repository": "https://alexisdinno.r-universe.dev", "Date/Publication": "2026-02-13 10:30:12 UTC", "RemoteUrl": "https://github.com/cran/paran", "RemoteRef": "HEAD", "RemoteSha": "429f645c14fc70b2355cac4f46d73586f50841e1", "_user": "alexisdinno", "_type": "src", "_file": "paran_1.5.5.tar.gz", "_fileid": "https://r2.ropensci.org/c3f99ca14790b925fa720597598e3bc31b94315c3ba1ae3aa474fef0579734ab", "_filesize": 148090, "_sha256": 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