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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 ff decomposes the sample space into cells where ff 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.

Keywords

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

R2 v1 2026-06-22T10:02:32.380Z