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Statistical nonparametric methods for the study of fossil populations

Published online by Cambridge University Press:  08 February 2016

Hervé Monchot and
Jacques Léchelle
Hervé Monchot
Affiliation:
Laboratoire d'Anthropologie, UMR 6569, Faculté de Médecine-Secteur Nord, Boulevard Pierre Dramard, F-13916 Marseille cedex 20, France. E-mail: Herve.Monchot@medecine.univ-mrs.fr
Jacques Léchelle
Affiliation:
Le Bel Ormeau, Bâtiment Q2, 422 avenue Jean-Paul Coste, F-13100 Aix-en-Provence, France. E-mail: Jacques.Lechelle@wanadoo.fr
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Abstract

The precise knowledge of the number and nature of the species belonging to a fossil assemblage as well as of the structure of each species (e.g., age, sex) is of great importance in paleontology. Mixture analysis based on the method of maximum likelihood is a modern statistical technique that concerns the problem of samples consisting of several components, the composition of which is not known. Nonparametric bootstrap and jackknife techniques are used to calculate a confidence interval for each estimated parameter (prior probability, mean, standard deviation) of each group. The bootstrap method is also used to evaluate mathematically how many groups are present in a sample. Experimental density smoothing using the kernel method appears to be a better solution than the use of histograms for the estimation of a distribution. This paper presents some basic concepts and procedures and discusses some preliminary results concerning sex ratios and mortality profile assessments using bones and tooth metric data of small (Ovis antiqua) and large (Bos primigenius) bovines from European Pleistocene sites.

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Articles
Information
Paleobiology , Volume 28 , Issue 1 , Winter 2002, pp. 55 - 69
Copyright
Copyright © The Paleontological Society 

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