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Optimal stratification and clustering on the line using the 1-norm

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  • Butler, Ronald W.

Abstract

A random sample of continuous measurements can be partitioned into g groups or clusters by minimizing the within group dispersion as measured by the 1-norm. The central limit theory associated with such partitions which are universally optimal or locally optimal is derived. A procedure is presented for determining the number of groups represented by the data based on a plot of a sequence of asymptotic nonparametric confidence intervals for the fractional reduction of within group error due to (g + 1)-clustering over g-clustering for g = 1, 2,....

Suggested Citation

  • Butler, Ronald W., 1986. "Optimal stratification and clustering on the line using the 1-norm," Journal of Multivariate Analysis, Elsevier, vol. 19(1), pages 142-155, June.
    • Handle: RePEc:eee:jmvana:v:19:y:1986:i:1:p:142-155
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    Cited by:

    1. Romo, Juan, 1992. "A rate of convergence in clustering analysis," UC3M Working papers. Economics 2884, Universidad Carlos III de Madrid. Departamento de Economía.

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