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Non-uniqueness in probabilistic numerical identification of bacteria

Part of: Multivariate analysis

Published online by Cambridge University Press:  14 July 2016

Mats Gyllenberg ,
Timo Koski ,
Edwin Reilink  and
Martin Verlaan
Mats Gyllenberg*
Affiliation:
Luleå University of Technology
Timo Koski*
Affiliation:
Luleå University of Technology
Edwin Reilink*
Affiliation:
University of Twente
Martin Verlaan*
Affiliation:
University of Twente
*
∗ Present address: Department of Applied Mathematics, University of Turku, FIN-20500 Turku, Finland.
∗∗ Postal address: Department of Applied Mathematics, Luleå University of Technology, S-95187 Luleå, Sweden.
∗∗∗ Postal address: Faculty of Applied Mathematics, University of Twente, 7500 AE Enschede, The Netherlands.
∗∗∗ Postal address: Faculty of Applied Mathematics, University of Twente, 7500 AE Enschede, The Netherlands.
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Abstract

In this note we point out an inherent difficulty in numerical identification of bacteria. The problem is that of uniqueness of the taxonomic structure or, in mathematical terms, the lack of statistical identifiability of finite mixtures of multivariate Bernoulli probability distributions shown here.

Keywords

MIXTURES OF DISTRIBUTIONSMULTIVARIATE BERNOULLI DISTRIBUTIONIDENTIFIABILITYNUMERICAL TAXONOMYGROUPING OF BACTERIA

MSC classification

Secondary: 62H30: Classification and discrimination; cluster analysis
Type
Short Communications
Information
Journal of Applied Probability , Volume 31 , Issue 2 , June 1994 , pp. 542 - 548
Copyright
Copyright © Applied Probability Trust 1994 

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