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: 0.1.0 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 Published: 2025-04-15 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 Documentation: Downloads: Reverse dependencies: Linking:Please use the canonical form https://CRAN.R-project.org/package=ScatterDensity to link to this page.
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