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) , and pareto density which was evaluated for univariate data by Thrun, Gehlert and Ultsch, 2020 . 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) .


Reference manual

It appears you don't have a PDF plugin for this browser. You can click here to download the reference manual.

install.packages("ScatterDensity")

0.1.1 by Michael Thrun, a year ago


https://www.deepbionics.org/


Report a bug at https://github.com/Mthrun/ScatterDensity/issues


Browse source code at https://github.com/cran/ScatterDensity


Authors: Michael Thrun [aut, cre, cph] (ORCID: , Felix Pape [aut, rev] , Luca Brinkman [aut] , Quirin Stier [aut]


Documentation:   PDF Manual  


GPL-3 license


Imports Rcpp, RcppParallel, pracma

Depends on methods

Suggests DataVisualizations, ggplot2, ggExtra, plotly, FCPS, parallelDist, secr, ClusterR, geometry

Linking to Rcpp, RcppArmadillo, RcppParallel


Suggested by BIDistances, DataVisualizations, PDEnaiveBayes, memshare.


See at CRAN