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Visualizing hypothesis tests in multivariate linear models: the heplots package for R

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Abstract

Hypothesis-error (or “HE”) plots, introduced by Friendly (J Stat Softw 17(6):1–42, 2006a; J Comput Graph Stat 16:421–444, 2006b), permit the visualization of hypothesis tests in multivariate linear models by representing hypothesis and error matrices of sums of squares and cross-products as ellipses. This paper describes the implementation of these methods in the heplots package for R, as well as their extension, for example from two to three dimensions and by scaling hypothesis ellipses and ellipsoids in a natural manner relative to error.

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Authors and Affiliations

  1. Department of Sociology, McMaster University, 1280 Main Street West, Hamilton, ON, Canada, L8S 4M4

    John Fox

  2. Department of Psychology, York University, Toronto, ON, Canada, M3J 1P3

    Michael Friendly

  3. Department of Mathematics and Statistics, York University, Toronto, ON, Canada, M3J 1P3

    Georges Monette

Authors
  1. John Fox
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  2. Michael Friendly
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  3. Georges Monette
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Corresponding author

Correspondence to John Fox.

Additional information

This is a paper for the proceedings of the Directions in Statistical Computing conference.

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Fox, J., Friendly, M. & Monette, G. Visualizing hypothesis tests in multivariate linear models: the heplots package for R. Comput Stat 24, 233–246 (2009). https://doi.org/10.1007/s00180-008-0120-1

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  • DOI: https://doi.org/10.1007/s00180-008-0120-1

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