清空筛选条件
清空筛选条件

varimax rotation of PCs

15 次查看（过去 30 天）
caterina
caterina 2013-3-2
Hi I need to rotate a PCs coming from a Principal Component Analysis. I know I shouldn't but the analysis I'm doing requests this step. I used function rotatefactors() but it does not produce the eingenvalues of the rotated PCs. At the same time I can't use factorian() routine because my covariance matrix is not positive definite. Does anyone have an idea? Thanks!
  1 个评论
Tom Lane
Tom Lane 2013-3-7
I would have thought that if you rotate the coordinate system away from the eigenvectors, then it is no longer meaningful to compute eigenvalues.

请先登录，再进行评论。

请先登录，再回答此问题。

采纳的回答

Tom Lane
Tom Lane 2013-3-8
On reflection, if you are thinking of the eigenvalues as the variances of the scores, perhaps this is what you want after rotation:
% Eigenvalues are the variances of the scores
load hald
[C,S,latent] = pca(ingredients);
V = cov(ingredients);
var(S) % variance of scores
latent' % latent values
Sigma = eig(V)' % eigenvalues
% Rotate away from the principal components
[L,T] = rotatefactors(C(:,1:2));
% Variances of the rotated scores, if we have S
var1 = diag(cov(S(:,1:2)*T))'
% Variances computed without using the scores
var2 = diag(L'*V*L)'

更多回答（1 个）

caterina
caterina 2013-3-10
Thank you very much! You helped me a lot. c.

类别

在 Help Center 和 File Exchange 中查找有关 Quadratic Programming and Cone Programming 的更多信息

标签

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!

Translated by