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svplots: Sample Variance Plots (Sv-Plots)

Two versions of sample variance plots, Sv-plot1 and Sv-plot2, will be provided illustrating the squared deviations from sample variance. Besides indicating the contribution of squared deviations for the sample variability, these plots are capable of detecting characteristics of the distribution such as symmetry, skewness and outliers. A remarkable graphical method based on Sv-plot2 can determine the decision on testing hypotheses over one or two population means. In sum, Sv-plots will be appealing visualization tools. Complete description of this methodology can be found in the article, Wijesuriya (2020) <doi:10.1080/03610918.2020.1851716>.

Version: 0.1.0
Depends: R (≥ 3.0.2)
Imports: ggplot2
Suggests: testthat (≥ 3.0.0), knitr, rmarkdown, stats
Published: 2021-04-07
DOI: 10.32614/CRAN.package.svplots
Author: Uditha Amarananda Wijesuriya
Maintainer: Uditha Amarananda Wijesuriya <u.wijesuriya at usi.edu>
License: GPL-3
NeedsCompilation: no
CRAN checks: svplots results

Documentation:

Reference manual: svplots.pdf
Vignettes: Sv-Plots and Testing Hypotheses

Downloads:

Package source: svplots_0.1.0.tar.gz
Windows binaries: r-devel: svplots_0.1.0.zip, r-release: svplots_0.1.0.zip, r-oldrel: svplots_0.1.0.zip
macOS binaries: r-release (arm64): svplots_0.1.0.tgz, r-oldrel (arm64): svplots_0.1.0.tgz, r-release (x86_64): svplots_0.1.0.tgz, r-oldrel (x86_64): svplots_0.1.0.tgz

Linking:

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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.