Hi,
I'm wondering if there's a way to determine how the (reduced) dimensions were calculated after running mds.
I'm thinking of something analagous to factor loadings in PCA. I understand that while PCA works on a correlation/covariance matrix of variables, MDS operates on a dissimilarity matrix of observations (right?) But I'm having trouble understanding why that should stop us from looking at the composition of the new, reduced dimensions the same way we look at the composition of the principal components.
-pca- repeatedly offers the loadings, but I've read through the -mds- and mds postestimation help files and I can't find anything close.
Thanks,
Dan
This email message is confidential and is intended only for the named recipient(s) above, and may contain information that is privileged, attorney work product or exempt from disclosure under applicable law. The contents of this email are for discussion purposes only and shall not create a legally binding commitment or agreement of EmSense Corporation, which shall require EmSense Corporation management approval and a formal written agreement signed by both parties. If you have received this message in error, or are not the named recipient(s), please immediately notify the sender and delete this message from your computer.
*
* For searches and help try:
* http://www.stata.com/help.cgi?search
* http://www.stata.com/support/statalist/faq
* http://www.ats.ucla.edu/stat/stata/
