Density Estimation and Visualization of 2D Scatter Plots R package ScatterDensity version 0.1.1 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>. Software 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 Michael Thrun <m.thrun@gmx.net> Comprehensive R Archive Network (CRAN) Michael Thrun [aut, cre, cph] (ORCID: <https://orcid.org/0000-0001-9542-5543>), Felix Pape [aut, rev], Luca Brinkman [aut], Quirin Stier [aut] (ORCID: <https://orcid.org/0000-0002-7896-4737>) GPL-3 2025-08-20 application/tgz https://CRAN.R-project.org/package=ScatterDensity doi:10.32614/CRAN.package.ScatterDensity