Sprache: Englisch
Verlag: Cambridge University Press, 2015
ISBN 10: 1107484316 ISBN 13: 9781107484313
Anbieter: Ria Christie Collections, Uxbridge, Vereinigtes Königreich
EUR 51,88
Anzahl: Mehr als 20 verfügbar
In den WarenkorbZustand: New. In.
Sprache: Englisch
Verlag: Cambridge University Press, 2015
ISBN 10: 1107484316 ISBN 13: 9781107484313
Anbieter: Kennys Bookstore, Olney, MD, USA
Zustand: New. A systematic introduction to a general nonparametric theory of statistics on manifolds, with emphasis on manifolds of shapes. Series: Institute of Mathematical Statistics Monographs. Num Pages: 252 pages, 20 b/w illus. BIC Classification: PBP; PBT. Category: (P) Professional & Vocational. Dimension: 229 x 152 x 13. Weight in Grams: 34. . 2015. Reprint. paperback. . . . . Books ship from the US and Ireland.
Sprache: Englisch
Verlag: Cambridge University Press, 2015
ISBN 10: 1107484316 ISBN 13: 9781107484313
Anbieter: Revaluation Books, Exeter, Vereinigtes Königreich
EUR 70,92
Anzahl: 2 verfügbar
In den WarenkorbPaperback. Zustand: Brand New. reprint edition. 252 pages. 9.00x6.00x0.75 inches. In Stock.
Sprache: Englisch
Verlag: Cambridge University Press, 2015
ISBN 10: 1107484316 ISBN 13: 9781107484313
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book introduces in a systematic manner a general nonparametric theory of statistics on manifolds, with emphasis on manifolds of shapes. The theory has important and varied applications in medical diagnostics, image analysis, and machine vision. An early chapter of examples establishes the effectiveness of the new methods and demonstrates how they outperform their parametric counterparts. Inference is developed for both intrinsic and extrinsic Fréchet means of probability distributions on manifolds, then applied to shape spaces defined as orbits of landmarks under a Lie group of transformations - in particular, similarity, reflection similarity, affine and projective transformations. In addition, nonparametric Bayesian theory is adapted and extended to manifolds for the purposes of density estimation, regression and classification. Ideal for statisticians who analyze manifold data and wish to develop their own methodology, this book is also of interest to probabilists, mathematicians, computer scientists, and morphometricians with mathematical training.