{ "_id": "6a1edc19b401979e7340fc39", "Package": "EFDR", "Type": "Package", "Title": "Wavelet-Based Enhanced FDR for Detecting Signals from Complete\nor Incomplete Spatially Aggregated Data", "Version": "1.3", "Date": "2023-08-23", "Authors@R": "c(person(\"Andrew\", \"Zammit-Mangion\", role = c(\"aut\", \"cre\"),\nemail = \"andrewzm@gmail.com\"),\nperson(\"Hsin-Cheng\", \"Huang\", role = \"aut\"))", "Description": "Enhanced False Discovery Rate (EFDR) is a tool to detect\nanomalies in an image. The image is first transformed into the\nwavelet domain in order to decorrelate any noise components,\nfollowing which the coefficients at each resolution are\nstandardised. Statistical tests (in a multiple hypothesis\ntesting setting) are then carried out to find the anomalies.\nThe power of EFDR exceeds that of standard FDR, which would\ncarry out tests on every wavelet coefficient: EFDR choose which\nwavelets to test based on a criterion described in Shen et al.\n(2002). The package also provides elementary tools to\ninterpolate spatially irregular data onto a grid of the\nrequired size. The work is based on Shen, X., Huang, H.-C., and\nCressie, N. 'Nonparametric hypothesis testing for a spatial\nsignal.' Journal of the American Statistical Association 97.460\n(2002): 1122-1140.", "URL": "https://github.com/andrewzm/EFDR/", "VignetteBuilder": "knitr", "License": "GPL (>= 2)", "Encoding": "UTF-8", "NeedsCompilation": "no", "RoxygenNote": "7.2.0", "Config/pak/sysreqs": "libabsl-dev cmake libgdal-dev gdal-bin libgeos-dev\nlibgsl0-dev libicu-dev libssl-dev libproj-dev libsqlite3-dev\nlibudunits2-dev", "Repository": "https://andrewzm.r-universe.dev", "Date/Publication": "2023-08-22 21:56:13 UTC", "RemoteUrl": "https://github.com/andrewzm/efdr", "RemoteRef": "HEAD", "RemoteSha": "cc20b56f1ea7571a79b38850c568dbbf25f3e753", "Packaged": { "Date": "2026-05-20 08:37:33 UTC", "User": "root" }, "Author": "Andrew Zammit-Mangion [aut, cre],\nHsin-Cheng Huang [aut]", "Maintainer": "Andrew Zammit-Mangion ", "MD5sum": "005ae9eb8bf5ee2dffc8427e90a23c82", "_user": "andrewzm", "_type": "src", "_file": "EFDR_1.3.tar.gz", "_fileid": "1c55316b51097a03e00c6d390bfb3a4ca3db5b3979aaa7c141b29648e1675d76", 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