Article

Journal of Classification

, Volume 11, Issue 1, pp 5-36

First online:

The MAP test for multimodality

  • Gregory Paul M. RozálAffiliated withDepartment of Statistics, Yale University
  • , J. A. HartiganAffiliated withDepartment of Statistics, Yale University

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Abstract

We introduce a test for detecting multimodality in distributions based on minimal constrained spanning trees. We define a Minimal Ascending Path Spanning Tree (MAPST) on a set of points as a spanning tree that has the minimal possible sum of lengths of links with the constraint that starting from any link, the lengths of the links are non-increasing towards a root node. We define similarly MAPSTs with more than one root. We present some algorithms for finding such trees. Based on these trees, we devise a test for multimodality, called the MAP Test (for Minimal Ascending Path). Using simulations, we estimate percentage points of the MAP statistic and assess the power of the test. Finally, we illustrate the use of MAPSTs for determining the number of modes in a distribution of positions of galaxies on photographic plates from a rich galaxy cluster.

Keywords

Minimal constrained spanning trees Nearest neighbor density estimates Minimal ascending path spanning trees Tests for modes The MAP test