k-Means Algorithm in Statistical Shape Analysis

References

• Amaral , G. J. A. , Dryden , I. L. , Wood , A. T. W. ( 2007 ). Pivotal bootstrap methods for k-sample problems in directional statistics and shape analysis . Journal of the American Statistical Association 102 : 695 – 707 .
   Web of Science ®Google Scholar
• Collette , B. B. ( 1965 ). Hemiramphidae (Pisces, Synentognathi) from tropical West Africa . Atlantide Reports 8 : 217 – 235 .
   Google Scholar
• Dryden , I. L. , Mardia , K. V. ( 1998 ). Statistical Shape Analysis . Chichester : Wiley & Sons .
   Google Scholar
• Goodall , C. R. ( 1991 ). Procrustes methods in the statistical analysis of shape (with discussion) . Journal of the Royal Statistical Society, Series B 53 : 285 – 339 .
   Google Scholar
• Gower , J. C. ( 1975 ). Generalized procrustes analysis . Psychometrika 40 : 33 – 50 .
   Web of Science ®Google Scholar
• Hartigan , J. A. ( 1975 ). Clustering Algorithms . New York : John Wiley & Sons .
   Google Scholar
• Hartigan , J. A. , Wong , M. A. ( 1979 ). A k-means clustering algorithm . Applied Statistics 28 : 100 – 108 .
   Google Scholar
• Hastie , T. , Tibshirani , R. , Friedman , J. ( 2001 ). The Elements of Statistical Learning . Canada : Springer .
   Google Scholar
• Johnson , R. A. , Wichern , D. W. ( 1992 ). Applied Multivariate Statistical Analysis . NJ : Prentice-Hall .
   Google Scholar
• Kendall , D. G. ( 1977 ). The diffusion of shape . Advances in Applied Probability 9 : 428 – 430 .
   Web of Science ®Google Scholar
• Kendall , D. G. ( 1984 ). Shape manifolds, procrustean metric and complex projective spaces . Bulletin of the London Mathematical Society 18 : 81 – 121 .
   Google Scholar
• Kendall , D. G. , Barden , D. , Carne , T. K. , Le , H. ( 1999 ). Shape and Shape Theory . London : John Wiley & Sons .
   Google Scholar
• Pennec , X. (1994). Probabilities and statistics on riemannian manifolds: basic tools for geometric measurements. IEEE Workshop on Nonlinear Signal and Image Processing 18:81–121.
   Google Scholar
• R Development Core Team. ( 2006 ). R: A Language and Environment for Statistical Computing . Vienna , Austria : R Foundation for Statistical Computing .
   Google Scholar
• Ripley , B. D. ( 1996 ). Pattern Recognition and Neural Networks . Cambridge : Cambridge University Press .
   Google Scholar
• Small , C. G. ( 1996 ). The Statistical Theory of Shape . New York : Springer-Verlag .
   Google Scholar
• Ziezold , H. ( 1994 ). Mean figures and mean shapes applied to biological figure and shape distribution in the plane . Biometrical Journal 36 : 491 – 510 .
   Google Scholar