Package: Modalclust 0.7

Modalclust: Hierarchical Modal Clustering

Performs Modal Clustering (MAC) including Hierarchical Modal Clustering (HMAC) along with their parallel implementation (PHMAC) over several processors. These model-based non-parametric clustering techniques can extract clusters in very high dimensions with arbitrary density shapes. By default clustering is performed over several resolutions and the results are summarised as a hierarchical tree. Associated plot functions are also provided. There is a package vignette that provides many examples. This version adheres to CRAN policy of not spanning more than two child processes by default.

Authors:Surajit Ray and Yansong Cheng

Modalclust_0.7.tar.gz
Modalclust_0.7.zip(r-4.7-any)Modalclust_0.7.zip(r-4.6-any)Modalclust_0.7.zip(r-4.5-any)
Modalclust_0.7.tgz(r-4.6-any)Modalclust_0.7.tgz(r-4.5-any)
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Modalclust_0.7.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
Modalclust/json (API)

# Install 'Modalclust' in R:

install.packages('Modalclust', repos = c('https://surajitstat.r-universe.dev', 'https://cloud.r-project.org'))

Datasets:

cta20 - Two dimensional data in original and log scale
cta20.hmac - Two dimensional data in original and log scale
disc2d - Two and three dimensional data representing two half discs
disc2d.hmac - Two and three dimensional data representing two half discs
disc3d - Two and three dimensional data representing two half discs
disc3d.hmac - Two and three dimensional data representing two half discs
logcta20 - Two dimensional data in original and log scale
logcta20.hmac - Two dimensional data in original and log scale
oned - One dimensional data with two main clusters
oned.hmac - One dimensional data with two main clusters

On CRAN:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

2.18 score 15 scripts 272 downloads 1 mentions 14 exports 5 dependencies

Last updated from:65647ef943. Checks:9 OK. Indexed: yes.

Target	Result	Time
linux-devel-x86_64	OK	112
source / vignettes	OK	191
linux-release-x86_64	OK	108
macos-release-arm64	OK	177
macos-oldrel-arm64	OK	132
windows-devel	OK	66
windows-release	OK	86
windows-oldrel	OK	99
wasm-release	OK	95

Exports:choose.cluster contour.hmac findmid hard.hmac hmac khat khat.inv modalclust mydmvnorm phmac plot.hmac sdofnorm soft.hmac summary.hmac

Dependencies:class lattice MASS mvtnorm zoo

Model based clustering via mode identification

Rendered fromModalclust.Rnwusingutils::Sweave

Last update: 2018-11-14
Started: 2014-01-16

Help page	Topics
Choosing the cluster which is closest to a specified point	choose.cluster
Plot clusters with different colors for two dimensional data overlayed on the contours of the original data.	contour contour.hmac
Two dimensional data in original and log scale	cta20 cta20.hmac logcta20 logcta20.hmac
Two and three dimensional data representing two half discs	disc2d disc2d.hmac disc3d disc3d.hmac
Find the mid point of memberships of each cluster	findmid
Plot clusters with different colors.	hard.hmac
Perform Modal Clustering in serial mode only	hmac
Calculate the smoothing paramters for implementation of Modal Clustering.	khat khat.inv sdofnorm
Calculate Density of Multivariate Normal for diagonal covariance	dmvnorm mydmvnorm
One dimensional data with two main clusters	oned oned.hmac
Main function for performing Modal Clusters either parallel or serial mode.	modalclust phmac
Plots of heierarchical tree for a 'hmac' object	plot plot.hmac
Plot soft clusters from Modal Clustering output	soft.hmac
Summary of HMAC output	summary summary.hmac

Package: Modalclust 0.7

Modalclust: Hierarchical Modal Clustering

Citation

Readme and manuals

Help Manual

Usage by other packages (reverse dependencies)