Journal of Classification

, Volume 11, Issue 1, pp 5–36

The MAP test for multimodality

Authors

  • Gregory Paul M. Rozál
    • Department of StatisticsYale University
  • J. A. Hartigan
    • Department of StatisticsYale University
Article

DOI: 10.1007/BF01201021

Cite this article as:
Rozál, G.P.M. & Hartigan, J.A. Journal of Classification (1994) 11: 5. doi:10.1007/BF01201021

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 treesNearest neighbor density estimatesMinimal ascending path spanning treesTests for modesThe MAP test

Copyright information

© Springer-Verlag 1994