{ "_id": "6a101d67acfb0bcc41c8a302", "Package": "Modalclust", "Type": "Package", "Title": "Hierarchical Modal Clustering", "Version": "0.7", "Date": "2018-11-11", "Author": "Surajit Ray and Yansong Cheng", "Maintainer": "Surajit Ray ", "Description": "Performs Modal Clustering (MAC) including Hierarchical\nModal Clustering (HMAC) along with their parallel\nimplementation (PHMAC) over several processors. These\nmodel-based non-parametric clustering techniques can extract\nclusters in very high dimensions with arbitrary density shapes.\nBy default clustering is performed over several resolutions and\nthe results are summarised as a hierarchical tree. Associated\nplot functions are also provided. There is a package vignette\nthat provides many examples. This version adheres to CRAN\npolicy of not spanning more than two child processes by\ndefault.", "License": "GPL-2", "Packaged": { "Date": "2026-05-14 07:54:26 UTC", "User": "root" }, "NeedsCompilation": "no", "Repository": "https://surajitstat.r-universe.dev", "Date/Publication": "2018-11-14 07:20:03 UTC", "RemoteUrl": "https://github.com/cran/Modalclust", "RemoteRef": "HEAD", "RemoteSha": "65647ef9439fc2ad46521ab1b6a85f77fc7fef45", "MD5sum": "d481a343427b939be6eec7e9c5de51a7", "_user": "surajitstat", "_type": "src", "_file": "Modalclust_0.7.tar.gz", "_fileid": "6737f3025937713d1477ae91a17b4f708a939e248d5c3be033f94267750f490e", "_filesize": 927306, "_sha256": "6737f3025937713d1477ae91a17b4f708a939e248d5c3be033f94267750f490e", "_created": "2026-05-14T07:54:26.000Z", "_published": "2026-05-22T09:09:59.150Z", "_distro": "noble", "_jobs": [ { "job": 77349946704, "time": 97, "config": "linux-devel-x86_64", "r": "4.7.0", "check": "OK", "artifact": "6989818266" }, { "job": 77349947029, 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"user", "name": "Surajit Ray" }, "_downloads": { "count": 169, "source": "https://cranlogs.r-pkg.org/downloads/total/last-month/Modalclust" }, "_mentions": 1, "_searchresults": 12, "_rbuild": "4.6.0", "_assets": [ "extra/citation.cff", "extra/citation.html", "extra/citation.json", "extra/citation.txt", "extra/contents.json", "extra/Modalclust.html", "manual.pdf" ], "_realowner": "surajitstat", "_cranurl": false, "_releases": [ { "version": "0.1", "date": "2010-11-13" }, { "version": "0.2", "date": "2012-01-15" }, { "version": "0.3", "date": "2012-05-02" }, { "version": "0.4", "date": "2013-06-25" }, { "version": "0.5", "date": "2014-01-17" }, { "version": "0.6", "date": "2014-05-23" }, { "version": "0.7", "date": "2018-11-14" } ], "_exports": [ "choose.cluster", "contour.hmac", "findmid", "hard.hmac", "hmac", "khat", "khat.inv", "modalclust", "mydmvnorm", "phmac", "plot.hmac", "sdofnorm", "soft.hmac", "summary.hmac" ], "_datasets": [ { "name": "cta20", "title": "Two dimensional data in 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clusters", "object": "oned.hmac", "file": "oned.hmac.rda", "class": [ "hmac" ], "fields": [], "table": false, "tojson": false } ], "_help": [ { "page": "choose.cluster", "title": "Choosing the cluster which is closest to a specified point", "topics": [ "choose.cluster" ] }, { "page": "contourHMAC", "title": "Plot clusters with different colors for two dimensional data overlayed on the contours of the original data.", "topics": [ "contour", "contour.hmac" ] }, { "page": "cta20", "title": "Two dimensional data in original and log scale", "topics": [ "cta20", "cta20.hmac", "logcta20", "logcta20.hmac" ] }, { "page": "disc2d", "title": "Two and three dimensional data representing two half discs", "topics": [ "disc2d", "disc2d.hmac", "disc3d", "disc3d.hmac" ] }, { "page": "findmid", "title": "Find the mid point of memberships of each cluster", "topics": [ "findmid" ] }, { "page": "hard.HMAC", "title": "Plot clusters with different colors.", "topics": [ "hard.hmac" ] }, { "page": "HMAC", 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