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Spatial Clustering of Neurons by Hypergeometric Disjoint Statistics

  • J. Krauth
Conference paper
Part of the Studies in Classification, Data Analysis, and Knowledge Organization book series (STUDIES CLASS)

Summary

Grimson and Rose (1991) suggested the use of a join—count statistic for detecting spatial clusters of neurons. We observe certain practical and theoretical difficulties in following this approach and propose instead the use of a maximum statistic. For this statistic, we derive in a similar way as for the disjoint statistic in Krauth (1991) exact upper and lower bounds for the upper tail probabilities. The procedure is illustrated by real data examples.

Keywords

Tail Probability Label Neuron Spatial Data Analysis Ciliary Ganglion Neighbour Object 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin · Heidelberg 1996

Authors and Affiliations

  • J. Krauth
    • 1
  1. 1.Department of PsychologyUniversity of DüsseldorfDüsseldorfGermany

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