ScatterDensity
0.1.1Density Estimation and Visualization of 2D Scatter Plots
Overview
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.
Install
Health
- OK2026-08-0513 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
- NOTE2026-08-0112 OK · 1 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
- OK2026-04-2214 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
- ERROR2026-04-1813 OK · 0 NOTE · 0 WARNING · 1 ERROR · 0 FAILURE
- OK2026-03-1014 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
Documentation
- Examples that run
- 100%
- Documented parameters
- 100%
- Return-value docs
- 100%
- References docs
- 40%
Downloads
Repository
Repository practices
1 development-tooling and community-health practice detected across 1 family in the upstream repository
Checks run against github.com/mthrun/scatterdensity on 2026-08-09.
Dependencies
Code & Tests
People & History
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Package metadata
- First published
- 2023-05-29
- Total releases
- 5 / 3 yrs
- License
- GPL-3 OSI
- Minimum R
- ≥ 2.10
- Download size
- 40 KB
- Installed size
- not tracked yet
- With dependencies
- not tracked yet
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