Statistical Inference using the Morse-Smale Complex
Statistics Theory
2017-04-05 v2 Methodology
Machine Learning
Statistics Theory
Abstract
The Morse-Smale complex of a function decomposes the sample space into cells where is increasing or decreasing. When applied to nonparametric density estimation and regression, it provides a way to represent, visualize, and compare multivariate functions. In this paper, we present some statistical results on estimating Morse-Smale complexes. This allows us to derive new results for two existing methods: mode clustering and Morse-Smale regression. We also develop two new methods based on the Morse-Smale complex: a visualization technique for multivariate functions and a two-sample, multivariate hypothesis test.
Cite
@article{arxiv.1506.08826,
title = {Statistical Inference using the Morse-Smale Complex},
author = {Yen-Chi Chen and Christopher R. Genovese and Larry Wasserman},
journal= {arXiv preprint arXiv:1506.08826},
year = {2017}
}
Comments
45 pages, 13 figures. Accepted to Electronic Journal of Statistics