# plotsubspace

##### Plots covariance matrices

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.

- Keywords
- hplot

##### 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.

##### See Also

##### Examples

```
# NOT RUN {
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
}
# }
```

*Documentation reproduced from package MCMCglmm, version 2.29, License: GPL (>= 2)*