bon said:
I'm trying to understand this a bit better..
so let M' be the diagonalised matrix of eigenvectors.. obviously AT = A if it is diagonal
if the eigenvectors that make up M are orthonormal, then surely either S-1MS or SMS-1 will work..
If the eigenvectors are not orthonormal, which one will be the one that gives the diagonalized version of M and why?
Thanks
I'll try to explain, but I'm not sure that I remember a really clean way to get this. Let [tex]\{ \mathbf{v}_i \}[/tex] be an orthonormal basis for M with associated eigenvalues [tex]\lambda_i[/tex]. Let S be the matrix that has the [tex]\mathbf{v}_i[/tex] as its columns, so
[tex]S = \begin{pmatrix} \mathbf{v}_1 & \mathbf{v}_2 & \cdots & \mathbf{v}_n \end{pmatrix}.[/tex]
By construction[tex]S^{-1} = S^T = \begin{pmatrix} \mathbf{v}_1^T \\ \mathbf{v}_2^T \\ \vdots \\ \mathbf{v}_n^T \end{pmatrix},[/tex]
which is the matrix with the [tex]\mathbf{v}_i^T[/tex] as its rows.
Then
[tex]M S = \begin{pmatrix}\lambda_1 \mathbf{v}_1 & \lambda_2\mathbf{v}_2 & \cdots &\lambda_n \mathbf{v}_n \end{pmatrix}[/tex]
and
[tex]S^T M S = \text{diag}~(\lambda_1, \ldots, \lambda_n) \equiv \Lambda.[/tex]
From this we conclude that, with the given choice of S,
[tex]M = S \Lambda S^T,[/tex]
while
[tex]S^T \Lambda S = M^T.[/tex]
In the case of your original question, R was symmetric, so these were equal. Also note that [tex]S M S^T[/tex] has no obvious special form.