Statistical Analysis of Persistence Intensity Functions
Methodology
2015-10-12 v1 Machine Learning
Abstract
Persistence diagrams are two-dimensional plots that summarize the topological features of functions and are an important part of topological data analysis. A problem that has received much attention is how deal with sets of persistence diagrams. How do we summarize them, average them or cluster them? One approach -- the persistence intensity function -- was introduced informally by Edelsbrunner, Ivanov, and Karasev (2012). Here we provide a modification and formalization of this approach. Using the persistence intensity function, we can visualize multiple diagrams, perform clustering and conduct two-sample tests.
Cite
@article{arxiv.1510.02502,
title = {Statistical Analysis of Persistence Intensity Functions},
author = {Yen-Chi Chen and Daren Wang and Alessandro Rinaldo and Larry Wasserman},
journal= {arXiv preprint arXiv:1510.02502},
year = {2015}
}
Comments
10 pages, 5 figures