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On the efficiency and sensitivity of a pyramidal classification algorithm

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Abstract

In this paper we propose a Pyramidal Classification Algorithm, which together with an appropriate aggregation index produces an indexed pseudo-hierarchy (in the strict sense) without inversions nor crossings. The computer implementation of the algorithm makes it possible to carry out some simulation tests by Monte Carlo methods in order to study the efficiency and sensitivity of the pyramidal methods of the Maximum, Minimum and UPGMA. The results shown in this paper may help to choose between the three classification methods proposed, in order to obtain the classification that best fits the original structure of the population, provided we have an a priori information concerning this structure.

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  • Àngel J. Gil & Carles Capdevila & Antoni Arcas, 1998. "On the efficiency and sensitivity of a pyramidal classification algorithm," Economics Working Papers 270, Department of Economics and Business, Universitat Pompeu Fabra.
    • Handle: RePEc:upf:upfgen:270
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    1. Wolfgang Gaul & Martin Schader, 1994. "Pyramidal classification based on incomplete dissimilarity data," Journal of Classification, Springer;The Classification Society, vol. 11(2), pages 171-193, September.
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      Keywords

      Pyramidal classification methods; aggregation index; pseudo-hierarchy; Robinsonian dissimilarity; Monte Carlo evaluation; overlapping clusters;
      All these keywords.

      JEL classification:

      • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
      • C88 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Other Computer Software

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