{ "_id": "6a2e6bca3efcd9bda431225c", "Package": "GLMaSPU", "Type": "Package", "Title": "An Adaptive Test on High Dimensional Parameters in Generalized\nLinear Models", "Version": "1.0", "Date": "2016-10-10", "Author": "Chong Wu and Wei Pan", "Maintainer": "Chong Wu ", "Description": "Several tests for high dimensional generalized linear\nmodels have been proposed recently. In this package, we\nimplemented a new test called adaptive sum of powered score\n(aSPU) for high dimensional generalized linear models, which is\noften more powerful than the existing methods in a wide\nscenarios. We also implemented permutation based version of\nseveral existing methods for research purpose. We recommend\nusers use the aSPU test for their real testing problem. You can\nlearn more about the tests implemented in the package via the\nfollowing papers: 1. Pan, W., Kim, J., Zhang, Y., Shen, X. and\nWei, P. (2014) A powerful and\nadaptive association test for rare variants, Genetics, 197(4).\n2. Guo, B., and Chen, S. X. (2016) .\nTests for high dimensional generalized linear models. Journal\nof the Royal Statistical Society: Series B. 3. Goeman, J. J.,\nVan Houwelingen, H. C., and Finos, L. (2011)\n. Testing against a high-dimensional\nalternative in the generalized linear model: asymptotic type I\nerror control. Biometrika, 98(2).", "License": "GPL-2", "RoxygenNote": "5.0.1", "NeedsCompilation": "yes", "Packaged": { "Date": "2026-06-14 08:49:09 UTC", "User": "root" }, "Repository": "https://cran.r-universe.dev", "Date/Publication": "2016-12-09 07:58:42 UTC", "RemoteUrl": "https://github.com/cran/GLMaSPU", "RemoteRef": "HEAD", "RemoteSha": "bb8114a03e28e9765fc0974f740e5f05d5ca11ba", "MD5sum": "da6ed5cfee9b13412f97417ce55b37f2", "_user": "cran", "_type": "src", "_file": "GLMaSPU_1.0.tar.gz", "_fileid": "846287379d368726c39eccb93213d3c5406f7ac141a8d69bd8313149fa1a8b2c", "_filesize": 114575, "_sha256": "846287379d368726c39eccb93213d3c5406f7ac141a8d69bd8313149fa1a8b2c", "_created": "2026-06-14T08:49:09.000Z", "_published": "2026-06-14T08:52:26.660Z", "_distro": "noble", "_jobs": [ { "job": 81263793601, "time": 109, "config": "linux-devel-arm64", "r": "4.7.0", "check": "OK", "artifact": "7619340013" }, { "job": 81263793588, "time": 121, "config": "linux-devel-x86_64", "r": "4.7.0", "check": "OK", 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"_realowner": "chongwu-biostat", "_cranurl": false, "_releases": [ { "version": "1.0", "date": "2016-12-09" } ], "_exports": [ "aSPU_apval", "aSPU_perm", "generate_data", "Goeman_perm", "HDGLM_perm" ], "_help": [ { "page": "GLMaSPU-package", "title": "An Adaptive Test on High Dimensional Parameters in Generalized Linear Models", "topics": [ "GLMaSPU-package", "GLMaSPU" ] }, { "page": "aSPU_apval", "title": "Asymptotic based Sum of Powered Score (SPU) tests and adaptive SPU (aSPU) test.", "topics": [ "aSPU_apval" ] }, { "page": "aSPU_perm", "title": "Resample based Sum of Powered Score (SPU) tests and adaptive SPU (aSPU) test.", "topics": [ "aSPU_perm" ] }, { "page": "generate_data", "title": "Generate data for generalized linear models in simulation.", "topics": [ "generate_data" ] }, { "page": "Goeman_perm", "title": "Resample based Goeman test.", "topics": [ "Goeman_perm" ] }, { "page": "HDGLM_perm", "title": "Resample based HDGLM test.", "topics": [ "HDGLM_perm" ] } ], "_rundeps": [ 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