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2018 Analysis of a mode clustering diagram
Isabella Verdinelli, Larry Wasserman
Electron. J. Statist. 12(2): 4288-4312 (2018). DOI: 10.1214/18-EJS1510


Mode-based clustering methods define clusters in terms of the modes of a density estimate. The most common mode-based method is mean shift clustering which defines clusters to be the basins of attraction of the modes. Specifically, the gradient of the density defines a flow which is estimated using a gradient ascent algorithm. Rodriguez and Laio (2014) introduced a new method that is faster and simpler than mean shift clustering. Furthermore, they define a clustering diagram that provides a simple, two-dimensional summary of the clustering information. We study the statistical properties of this diagram and we propose some improvements and extensions. In particular, we show a connection between the diagram and robust linear regression.


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Isabella Verdinelli. Larry Wasserman. "Analysis of a mode clustering diagram." Electron. J. Statist. 12 (2) 4288 - 4312, 2018.


Received: 1 May 2018; Published: 2018
First available in Project Euclid: 18 December 2018

zbMATH: 07003244
MathSciNet: MR3892341
Digital Object Identifier: 10.1214/18-EJS1510

Primary: 62H30
Secondary: 62H86


Vol.12 • No. 2 • 2018
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