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: |
0.1.1 |
| Depends: |
methods, R (≥ 2.10) |
| Imports: |
Rcpp, RcppParallel (≥ 5.1.4), pracma |
| LinkingTo: |
Rcpp, RcppArmadillo, RcppParallel |
| Suggests: |
DataVisualizations, ggplot2, ggExtra, plotly, FCPS, parallelDist, secr, ClusterR, geometry |
| Published: |
2025-08-20 |
| DOI: |
10.32614/CRAN.package.ScatterDensity |
| Author: |
Michael Thrun 
[aut, cre, cph],
Felix Pape [aut, rev],
Luca Brinkman [aut],
Quirin Stier
[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 |