%0 Journal Article %1 john2009visualizing %A Fox, John %A Friendly, Michael %A Monette, Georges %D 2009 %J Computational Statistics %K R hypothesis multivariate package tests %N 2 %P 233--246 %T Visualizing hypothesis tests in multivariate linear models: the heplots package for R %U http://dx.doi.org/10.1007/s00180-008-0120-1 %V 24 %X 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 matricesof 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 andellipsoids in a natural manner relative to error.

@article{john2009visualizing, abstract = {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 matricesof 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 andellipsoids in a natural manner relative to error.}, added-at = {2010-06-07T10:15:57.000+0200}, author = {Fox, John and Friendly, Michael and Monette, Georges}, biburl = {https://www.bibsonomy.org/bibtex/2cb610fc2f8c064255bb74132c9feba7d/vivion}, description = {SpringerLink - Journal Article}, interhash = {6859465f75cb39987dcbd23d8be43859}, intrahash = {cb610fc2f8c064255bb74132c9feba7d}, journal = {Computational Statistics}, keywords = {R hypothesis multivariate package tests}, month = {#may#}, number = 2, pages = {233--246}, timestamp = {2010-06-07T10:15:57.000+0200}, title = {Visualizing hypothesis tests in multivariate linear models: the heplots package for R}, url = {http://dx.doi.org/10.1007/s00180-008-0120-1}, volume = 24, year = 2009 }