Visualizing Hypothesis Tests in Multivariate Linear Models
Draw a 3D Arrow in an RGL Scene
Bartlett Tests of Homogeneity of Variances
Find the bounding box of a rgl::mesh3d or rgl::qmesh3d object
Box's M-test
Coefficient plots for Multivariate Linear Models
Calculate column deviations from central values
Draw classical and robust covariance ellipses for one or more groups
Chi Square Quantile-Quantile plots
Draw a 3D cross in an rgl scene
Find degrees of freedom for model terms
Draw Axes of a 2D Covariance Ellipse
Draw Conjugate Axes and Parallelogram Surrounding a Covariance Ellipse
Draw axes of a 3D ellipsoid
Draw an Ellipsoid in an rgl Scene
Measures of Partial Association (Eta-squared) for Linear Models
Glance at an mlm object
Orthogonalize successive columns of a data frame or matrix
Two-Dimensional HE Plots
One-Dimensional HE Plots
Three-Dimensional HE Plots
Internal heplots functions
Visualizing Hypothesis Tests in Multivariate Linear Models
Plot an Interpolation Between Two Related Data Sets
Label an ellipse
Levene Tests of Homogeneity of Variances
Calculate confidence interval for log determinant of covariance matric...
Classical and Robust Mahalanobis Distances
Mark a point null hypothesis in an HE plot
Pairwise HE Plots
Plot for Box's M test and generalizations
Plot observation weights from a robust multivariate linear models
Response Speed in a Probe Experiment
Robust Fitting of Multivariate Linear Models
Calculate statistics for levels of factors
Calculate Means for a Term in a Multivariate Linear Model
Make Colors Transparent
Provides HE plot and other functions for visualizing hypothesis tests in multivariate linear models. HE plots represent sums-of-squares-and-products matrices for linear hypotheses and for error using ellipses (in two dimensions) and ellipsoids (in three dimensions). The related 'candisc' package provides visualizations in a reduced-rank canonical discriminant space when there are more than a few response variables.
Useful links