plotsubspace: Plots covariance matrices

In MCMCglmm: MCMC Generalised Linear Mixed Models

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 [e-mail] with code taken from the rgl package

See Also

rgl

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 documentation built on July 9, 2023, 5:24 p.m.