Document Type
Article
Publication Date
12-1999
Abstract
The k-means algorithm and the principal curve algorithm are special cases of a self-consistency algorithm. A general self-consistency algorithm is described and results are provided describing the behavior of the algorithm for theoretical distributions, in particular elliptical distributions. The results are used to contrast the behavior of the algorithms when applied to a theoretical model and when applied to finite datasets from the model. The algorithm is also used to determine principal loops for the bivariate normal distribution.
Repository Citation
Tarpey, T.
(1999). Self-Consistency Algorithms. Journal of Computational and Graphical Statistics, 8 (4), 889-905.
https://corescholar.libraries.wright.edu/math/12
DOI
10.2307/1390832
Comments
Original publication is available at http://www.tandfonline.com/doi/abs/10.1080/10618600.1999.10474854