tt: Treelet transform with Stata
Abstract
The treelet transform is a recent data reduction technique from the field of machine learning. Sharing many similarities with principal component analysis, the treelet transform can reduce a multidimensional dataset to the projections on a small number of directions or components that account for much of the variation in the original data. However, in contrast to principal component analysis, the treelet transform produces sparse components. This can greatly simplify interpretation. I describe the tt Stata add-on for performing the treelet transform. The add- on includes a Mata implementation of the treelet transform algorithm alongside other functionality to aid in the practical application of the treelet transform. I demonstrate an example of a basic exploratory data analysis using the tt add-on. Copyright 2012 by StataCorp LP.Download Info
If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.Bibliographic Info
Article provided by StataCorp LP in its journal Stata Journal.
Volume (Year): 12 (2012)
Issue (Month): 1 (March)
Pages: 130-146
Note: to access software from within Stata, net describe http://www.stata-journal.com/software/sj12-1/st0249/
Contact details of provider:
Web page: http://www.stata-journal.com/
Order Information:
Web: http://www.stata-journal.com/subscription.html
Related research
Keywords: tt; ttcv; ttscree; ttdendro; ttloading; ttpredict; ttstab; treelet; principal component analysis; dimension reduction; factor analysis;References
No references listed on IDEASYou can help add them by filling out this form.
Citations
Lists
This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.Statistics
Access and download statisticsCorrections
When requesting a correction, please mention this item's handle: RePEc:tsj:stataj:v:12:y:2012:i:1:p:130-146For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Christopher F. Baum) or (Lisa Gilmore).
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If references are entirely missing, you can add them using this form.
If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.
Please note that corrections may take a couple of weeks to filter through the various RePEc services.

