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>.
||methods, R (≥ 2.10)
||DataVisualizations, ggplot2, ggExtra, plotly, FCPS, parallelDist, secr, ClusterR
[aut, cre, cph],
Felix Pape [aut, rev],
Luca Brinkman [aut],
||Michael Thrun <m.thrun at gmx.net>
||ScatterDensity citation info
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