ggplot2 Compatible Quantile-Quantile Plots in R

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.

Alexandre Almeida , Adam Loy , Heike Hofmann

Supplementary materials

Supplementary materials are available in addition to this article. It can be downloaded at

CRAN packages used

base, lattice, car, ggplot2, qqplotr, stats, robustbase, boot

CRAN Task Views implied by cited packages

Multivariate, Econometrics, Graphics, Robust, SocialSciences, Finance, Optimization, Phylogenetics, Survival, TimeSeries


Text and figures are licensed under Creative Commons Attribution CC BY 4.0. The figures that have been reused from other sources don't fall under this license and can be recognized by a note in their caption: "Figure from ...".


For attribution, please cite this work as

Almeida, et al., "The R Journal: ggplot2 Compatible Quantile-Quantile Plots in R", The R Journal, 2018

BibTeX citation

  author = {Almeida, Alexandre and Loy, Adam and Hofmann, Heike},
  title = {The R Journal: ggplot2 Compatible Quantile-Quantile Plots in R},
  journal = {The R Journal},
  year = {2018},
  note = {},
  doi = {10.32614/RJ-2018-051},
  volume = {10},
  issue = {2},
  issn = {2073-4859},
  pages = {248-261}