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ScatterDensity (version 0.1.1)

Density Estimation and Visualization of 2D Scatter Plots

Description

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) .

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Version

Install

install.packages('ScatterDensity')

Monthly Downloads

342

Version

0.1.1

License

GPL-3

Maintainer

Michael Thrun

Last Published

August 20th, 2025

Functions in ScatterDensity (0.1.1)

SampleScatter

takes a sample for a scatter plot
inPSphere2D

2D data points in Pareto Sphere
fast_table_num

fast_table_num
ScatterDensity-package

tools:::Rd_package_title("ScatterDensity")
PolygonGate

PolygonGate
DensityScatter.DDCAL

Scatter density plot [Brinkmann et al., 2023]
DDCAL

Density Distribution Cluster Algorithm of [Lux and Rinderle-Ma, 2023].
SmoothedDensitiesXY

Smoothed Densities X with Y
PDEscatter

Scatter Density Plot
PointsInPolygon

PointsInPolygon