Probabilistic Fréchet means for time varying persistence diagrams


Autoria(s): Munch, E; Turner, K; Bendich, P; Mukherjee, S; Mattingly, J; Harer, J
Data(s)

01/01/2015

Formato

1173 - 1204

Identificador

Electronic Journal of Statistics, 2015, 9 pp. 1173 - 1204

1935-7524

http://hdl.handle.net/10161/10051

http://hdl.handle.net/10161/10051

Relação

Electronic Journal of Statistics

10.1214/15-EJS1030

Palavras-Chave #Topological data analysis #Frechet mean #time varying data
Tipo

Journal Article

Resumo

© 2015, Institute of Mathematical Statistics. All rights reserved.In order to use persistence diagrams as a true statistical tool, it would be very useful to have a good notion of mean and variance for a set of diagrams. In [23], Mileyko and his collaborators made the first study of the properties of the Fréchet mean in (D<inf>p</inf>, W<inf>p</inf>), the space of persistence diagrams equipped with the p-th Wasserstein metric. In particular, they showed that the Fréchet mean of a finite set of diagrams always exists, but is not necessarily unique. The means of a continuously-varying set of diagrams do not themselves (necessarily) vary continuously, which presents obvious problems when trying to extend the Fréchet mean definition to the realm of time-varying persistence diagrams, better known as vineyards. We fix this problem by altering the original definition of Fréchet mean so that it now becomes a probability measure on the set of persistence diagrams; in a nutshell, the mean of a set of diagrams will be a weighted sum of atomic measures, where each atom is itself a persistence diagram determined using a perturbation of the input diagrams. This definition gives for each N a map (D<inf>p</inf>)<sup>N</sup>→ℙ(D<inf>p</inf>). We show that this map is Hölder continuous on finite diagrams and thus can be used to build a useful statistic on vineyards.