mlsanityData to 7 Oct 2026

The modal age of Statistics

arXiv 1807.02789 ↗First posted 8 Jul 2018stat.ME stat.MLcited by 9

Not on the map. Why?

Abstract (arXiv)

Recently, a number of statistical problems have found an unexpected solution by inspecting them through a "modal point of view". These include classical tasks such as clustering or regression. This has led to a renewed interest in estimation and inference for the mode. This paper offers an extensive survey of the traditional approaches to mode estimation and explores the consequences of applying this modern modal methodology to other, seemingly unrelated, fields.

Key facts. Cited by 9 papers in the map (data through 7 Oct 2026). First posted on arXiv 8 Jul 2018.

Builds on

No reference list yet.

Built on by

Cited by year

Citing papers per year: 2021: 4; 2022: 2; 2023: 1; 2024: 1; 2025: 1.

9 papers.

  1. 2021Moving Up the Cluster Tree with the Gradient Flowcited by 3
  2. 2024An Axiomatic Definition of Hierarchical Clusteringcited by 3
  3. 2021The EM Perspective of Directional Mean Shift Algorithmcited by 1
  4. 2021Mode and Ridge Estimation in Euclidean and Directional Product Spaces: A Mean Shift Approachcited by 1
  5. 2021An Asymptotic Equivalence between the Mean-Shift Algorithm and the Cluster Treecited by 1
  6. 2022Bump hunting through density curvature featurescited by 0
  7. 2022Bagged k-Distance for Mode-Based Clustering Using the Probability of Localized Level Setscited by 0
  8. 2023Bayesian taut splines for estimating the number of modescited by 0
  9. 2025Testing-driven Variable Selection in Bayesian Modal Regressioncited by 0