The R Journal: article published in 2018, volume 10:2

ggplot2 Compatible Quantile-Quantile Plots in R PDF download
Alexandre Almeida, Adam Loy and Heike Hofmann , The R Journal (2018) 10:2, pages 248-261.

Abstract Q-Q plots allow us to assess univariate distributional assumptions by comparing a set of quantiles from the empirical and the theoretical distributions in the form of a scatterplot. To aid in the interpretation of Q-Q plots, reference lines and confidence bands are often added. We can also detrend the Q-Q plot so the vertical comparisons of interest come into focus. Various implementations of Q-Q plots exist in R, but none implements all of these features. qqplotr extends ggplot2 to provide a complete implementation of Q-Q plots. This paper introduces the plotting framework provided by qqplotr and provides multiple examples of how it can be used.

Received: 2017-12-20; online 2018-12-07, supplementary material, (2.4 Kb)
CRAN packages: base, lattice, car, ggplot2, qqplotr, stats, robustbase, boot
CRAN Task Views implied by cited CRAN packages: Multivariate, Econometrics, Graphics, Robust, SocialSciences, Finance, Optimization, Phylogenetics, Survival, TimeSeries


CC BY 4.0
This article and supplementary materials are licensed under a Creative Commons Attribution 4.0 International license.

@article{RJ-2018-051,
  author = {Alexandre Almeida and Adam Loy and Heike Hofmann},
  title = {{ggplot2 Compatible Quantile-Quantile Plots in R}},
  year = {2018},
  journal = {{The R Journal}},
  doi = {10.32614/RJ-2018-051},
  url = {https://doi.org/10.32614/RJ-2018-051},
  pages = {248--261},
  volume = {10},
  number = {2}
}