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This approach offers robust\nestimations that effectively counteract the mentioned problems,\nand its effectiveness remains consistent regardless of the\nsample size.", "License": "MIT + file LICENSE", "Encoding": "UTF-8", "RoxygenNote": "7.3.1", "Maintainer": "Xuekui Zhang ", "NeedsCompilation": "no", "Packaged": { "Date": "2026-10-21 09:55:32 UTC", "User": "root" }, "Author": "Xuekui Zhang [aut, cre], Li Xing [aut], Jing Zhang [aut],\nSoojeong Kim [aut]", "Repository": "https://ubcxzhang.r-universe.dev", "Date/Publication": "2024-03-13 02:33:43 UTC", "RemoteUrl": "https://github.com/cran/glmpermu", "RemoteRef": "HEAD", "RemoteSha": "a6490814ae2ffc14b012dc28bb412b9619402335", "_user": "ubcxzhang", "_type": "src", "_file": "glmpermu_0.0.1.tar.gz", "_fileid": "https://r2.ropensci.org/2ef2dc6807829e5f49ce42f43bc863d890cceea2a68c9482e8d9e9d3a59d5e50", "_filesize": 98720, "_sha256": "2ef2dc6807829e5f49ce42f43bc863d890cceea2a68c9482e8d9e9d3a59d5e50", "_expires": "2027-01-29T09:57:43.000Z", 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