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>.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
0.1.1 |
2026-04-09 windows/windows R-4.5 | ScatterDensity_0.1.1.zip |
610.4 KiB |