adaplots: Ada-Plot and Uda-Plot for Assessing Distributional Attributes and Normality

The centralized empirical cumulative average deviation function is utilized to develop both Ada-plot and Uda-plot as alternatives to Ad-plot and Ud-plot introduced by the author. Analogous to Ad-plot, Ada-plot can identify symmetry, skewness, and outliers of the data distribution. The Uda-plot is as exceptional as Ud-plot in assessing normality. The d-value that quantifies the degree of proximity between the Uda-plot and the graph of the estimated normal density function helps guide to make decisions on confirmation of normality. Extreme values in the data can be eliminated using the 1.5IQR rule to create its robust version if user demands. Full description of the methodology can be found in the article by Wijesuriya (2025a) <doi:10.1080/03610926.2025.2558108>. Further, the development of Ad-plot and Ud-plot is contained in both article and the 'adplots' R package by Wijesuriya (2025b & 2025c) <doi:10.1080/03610926.2024.2440583> and <doi:10.32614/CRAN.package.adplots>.

Version: 0.1.0
Imports: ggplot2
Suggests: knitr, rmarkdown, testthat (≥ 3.0.0)
Published: 2025-10-06
DOI: 10.32614/CRAN.package.adaplots (may not be active yet)
Author: Uditha Amarananda Wijesuriya [aut, cre]
Maintainer: Uditha Amarananda Wijesuriya <u.wijesuriya at usi.edu>
License: GPL-3
NeedsCompilation: no
CRAN checks: adaplots results

Documentation:

Reference manual: adaplots.html , adaplots.pdf
Vignettes: Ada-Plot and Uda-Plot (source, R code)

Downloads:

Package source: adaplots_0.1.0.tar.gz
Windows binaries: r-devel: adaplots_0.1.0.zip, r-release: not available, r-oldrel: not available
macOS binaries: r-release (arm64): not available, r-oldrel (arm64): not available, r-release (x86_64): adaplots_0.1.0.tgz, r-oldrel (x86_64): adaplots_0.1.0.tgz

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