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Empirical likelihood methods for two-dimensional shape analysis

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  • Getulio J. A. Amaral
  • Andrew T. A. Wood

Abstract

We consider empirical likelihood for the mean similarity shape of objects in two dimensions described by labelled landmarks. The restriction to two dimensions permits the representation of preshapes as complex unit vectors. We focus on the use of empirical likelihood techniques for the construction of confidence regions for the mean shape and for testing the hypothesis of a common mean shape across several populations. Theoretical properties and computational details are discussed and the results of a simulation study are presented. Our results show that bootstrap calibrated empirical likelihood performs well in practice in the planar shape setting. Copyright 2010, Oxford University Press.

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  • Getulio J. A. Amaral & Andrew T. A. Wood, 2010. "Empirical likelihood methods for two-dimensional shape analysis," Biometrika, Biometrika Trust, vol. 97(3), pages 757-764.
    • Handle: RePEc:oup:biomet:v:97:y:2010:i:3:p:757-764
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    File URL: http://hdl.handle.net/10.1093/biomet/asq028
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    Cited by:

    1. Tsagris, Michail & Preston, Simon & T.A. Wood, Andrew, 2016. "Nonparametric hypothesis testing for equality of means on the simplex," MPRA Paper 72771, University Library of Munich, Germany.

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