Statistics, Department of
The R Journal
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Date of this Version
12-2018
Document Type
Article
Citation
The R Journal (December 2018) 10(2); Editor: John Verzani
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.
Included in
Numerical Analysis and Scientific Computing Commons, Programming Languages and Compilers Commons
Comments
Copyright 2018, The R Foundation. Open access material. License: CC BY 4.0 International