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ScatterDensity

Density Estimation and Visualization of 2D Scatter Plots

v0.1.1 · Aug 20, 2025 · GPL-3

Description

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>.

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r-devel-linux-x86_64-fedora-gcc OK
r-devel-macos-arm64 OK
r-devel-windows-x86_64 OK
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r-oldrel-windows-x86_64 OK
r-patched-linux-x86_64 OK
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r-release-windows-x86_64 OK
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Check History

OK 14 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE Mar 9, 2026

Reverse Dependencies (3)

Dependency Network

Dependencies Reverse dependencies Rcpp RcppParallel pracma DataVisualizations PDEnaiveBayes memshare ScatterDensity

Version History

new 0.1.1 Mar 9, 2026