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ScatterDensity: Density Estimation and Visualization of 2D Scatter Plots

The user has the option to utilize the two-dimensional density estimation techniques called smoothed density published by Eilers and Goeman (2004) <doi:10.1093/bioinformatics/btg454>, and pareto density which was evaluated for univariate data by Thrun, Gehlert and Ultsch, 2020 <doi:10.1371/journal.pone.0238835>. Moreover, it provides visualizations of the density estimation in the form of two-dimensional scatter plots in which the points are color-coded based on increasing density. Colors are defined by the one-dimensional clustering technique called 1D distribution cluster algorithm (DDCAL) published by Lux and Rinderle-Ma (2023) <doi:10.1007/s00357-022-09428-6>.

Version: 0.0.4
Depends: methods, R (≥ 2.10)
Imports: Rcpp, pracma
LinkingTo: Rcpp, RcppArmadillo
Suggests: DataVisualizations, ggplot2, ggExtra, plotly, FCPS, parallelDist, secr, ClusterR
Published: 2023-10-09
DOI: 10.32614/CRAN.package.ScatterDensity
Author: Michael Thrun ORCID iD [aut, cre, cph], Felix Pape [aut, rev], Luca Brinkman [aut], Quirin Stier ORCID iD [aut]
Maintainer: Michael Thrun <m.thrun at gmx.net>
BugReports: https://github.com/Mthrun/ScatterDensity/issues
License: GPL-3
URL: https://www.deepbionics.org/
NeedsCompilation: yes
Citation: ScatterDensity citation info
CRAN checks: ScatterDensity results

Documentation:

Reference manual: ScatterDensity.pdf

Downloads:

Package source: ScatterDensity_0.0.4.tar.gz
Windows binaries: r-devel: ScatterDensity_0.0.4.zip, r-release: ScatterDensity_0.0.4.zip, r-oldrel: ScatterDensity_0.0.4.zip
macOS binaries: r-release (arm64): ScatterDensity_0.0.4.tgz, r-oldrel (arm64): ScatterDensity_0.0.4.tgz, r-release (x86_64): ScatterDensity_0.0.4.tgz, r-oldrel (x86_64): ScatterDensity_0.0.4.tgz
Old sources: ScatterDensity archive

Reverse dependencies:

Reverse suggests: DataVisualizations

Linking:

Please use the canonical form https://CRAN.R-project.org/package=ScatterDensity to link to this page.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.