Parametric Inference using Persistence Diagrams: A Case Study in Population Genetics
Quantitative Methods
2014-06-19 v1
Abstract
Persistent homology computes topological invariants from point cloud data. Recent work has focused on developing statistical methods for data analysis in this framework. We show that, in certain models, parametric inference can be performed using statistics defined on the computed invariants. We develop this idea with a model from population genetics, the coalescent with recombination. We apply our model to an influenza dataset, identifying two scales of topological structure which have a distinct biological interpretation.
Cite
@article{arxiv.1406.4582,
title = {Parametric Inference using Persistence Diagrams: A Case Study in Population Genetics},
author = {Kevin Emmett and Daniel Rosenbloom and Pablo Camara and Raul Rabadan},
journal= {arXiv preprint arXiv:1406.4582},
year = {2014}
}
Comments
5 pages, 4 figures. Prepared for the ICML 2014 Workshop on Topological Methods in Machine Learning