English

Local angles and dimension estimation from data on manifolds

Statistics Theory 2018-05-07 v1 Machine Learning Statistics Theory

Abstract

For data living in a manifold MRmM\subseteq \mathbb{R}^m and a point pMp\in M we consider a statistic Uk,nU_{k,n} which estimates the variance of the angle between pairs of vectors XipX_i-p and XjpX_j-p, for data points XiX_i, XjX_j, near pp, and evaluate this statistic as a tool for estimation of the intrinsic dimension of MM at pp. Consistency of the local dimension estimator is established and the asymptotic distribution of Uk,nU_{k,n} is found under minimal regularity assumptions. Performance of the proposed methodology is compared against state-of-the-art methods on simulated data.

Keywords

Cite

@article{arxiv.1805.01577,
  title  = {Local angles and dimension estimation from data on manifolds},
  author = {Mateo Díaz and Adolfo J. Quiroz and Mauricio Velasco},
  journal= {arXiv preprint arXiv:1805.01577},
  year   = {2018}
}

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R2 v1 2026-06-23T01:44:46.062Z