MCMCglmm: plotsubspace – R documentation

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plotsubspace

Plots covariance matrices

Description

Represents covariance matrices as 3-d ellipsoids using the rgl package. Covariance matrices of dimension greater than 3 are plotted on the subspace defined by the first three eigenvectors.

Usage

plotsubspace(CA, CB=NULL, corr = FALSE, shadeCA = TRUE, 
      shadeCB = TRUE, axes.lab = FALSE, ...)

Arguments

`CA`	Matrix
`CB`	Optional second matrix
`corr`	If `TRUE` the covariance matrices are transformed into correlation matrices
`shadeCA`	If `TRUE` the ellipsoid is solid, if `FALSE` the ellipsoid is wireframe
`shadeCB`	If `TRUE` the ellipsoid is solid, if `FALSE` the ellipsoid is wireframe
`axes.lab`	If `TRUE` the axes are labelled with the eigenvectors
`...`	further arguments to be passed

Details

The matrix CA is always red, and the matrix CB if given is always blue. The subspace is defined by the first three eigenvectors of CA, and the percentage of variance for each matrix along these three dimensions is given in the plot title.

Author(s)

Jarrod Hadfield j.hadfield@ed.ac.uk with code taken from the rgl package

Examples

if(requireNamespace("rgl")!=FALSE){
   G1<-rIW(diag(4),10)
   G2<-G1*1.2
 #  plotsubspace(G1, G2, shadeCB=FALSE)
 # commented out because of problems with rgl 
 }

MCMCglmm

MCMC Generalised Linear Mixed Models

v2.32

GPL (>= 2)

Authors

Jarrod Hadfield

Initial release

2021-03-12