Home  >>  Archives  >>  Volume 12 Number 1  >>  st0249

The Stata Journal
Volume 12 Number 1: pp. 130-146



Subscribe to the Stata Journal
cover

tt: Treelet transform with Stata

Anders Gorst-Rasmussen
Department of Mathematical Sciences
Aalborg University
Aalborg, Denmark
[email protected]
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.
Terms of use     View this article (PDF)

View all articles by this author: Anders Gorst-Rasmussen

View all articles with these keywords: tt, ttcv, ttscree, ttdendro, ttloading, ttpredict, ttstab, treelet, principal component analysis, dimension reduction, factor analysis

Download citation: BibTeX  RIS

Download citation and abstract: BibTeX  RIS