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  • 1
    UID:
    b3kat_BV041826188
    Format: XIII, 237 S. , graph. Darst. , 23 cm
    Edition: 1. publ.
    ISBN: 9781107019584 , 1107019583
    Series Statement: Institute of Mathematical Statistics monographs 2
    Note: Includes bibliographical references (p. 229-234) and index
    Language: English
    Subjects: Mathematics
    RVK:
    Keywords: Nichtparametrische Statistik ; Inferenzstatistik ; Mannigfaltigkeit
    Library Location Call Number Volume/Issue/Year Availability
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  • 2
    UID:
    gbv_883358107
    Format: 1 Online-Ressource (xiii, 237 pages) , digital, PDF file(s)
    ISBN: 9781139094764
    Series Statement: Institute of Mathematical Statistics monographs 2
    Content: 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
    Content: Introduction -- Examples -- Location and spread on metric spaces -- Extrinsic analysis on manifolds -- Intrinsic analysis on manifolds -- Landmark-based shape spaces -- Kendall's similarity shape spaces [characters omitted] -- The planar shape space [characters omitted] -- Reflection similarity shape spaces R[characters omitted] -- Stiefel manifolds V[characters omitted] -- Affine shape spaces A[characters omitted] -- Real projective spaces and projective shape spaces -- Nonparametric Bayes inference on manifolds -- Nonparametric Bayes regression, classification and hypothesis testing on manifolds -- Appendixes: A. Differentiable manifolds -- B. Riemannian manifolds -- C. Dirichlet processes -- D. Parametric models on S[character omitted] and [characters omitted]
    Note: Title from publisher's bibliographic system (viewed on 05 Oct 2015)
    Additional Edition: ISBN 9781107019584
    Additional Edition: ISBN 9781107484313
    Additional Edition: Erscheint auch als Druck-Ausgabe ISBN 9781107019584
    Language: English
    Library Location Call Number Volume/Issue/Year Availability
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  • 3
    Online Resource
    Online Resource
    Cambridge :Cambridge University Press,
    UID:
    almahu_9948233733502882
    Format: 1 online resource (xiii, 237 pages) : , digital, PDF file(s).
    ISBN: 9781139094764 (ebook)
    Series Statement: Institute of Mathematical Statistics monographs ; 2
    Content: 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.
    Note: Title from publisher's bibliographic system (viewed on 05 Oct 2015). , Introduction -- Examples -- Location and spread on metric spaces -- Extrinsic analysis on manifolds -- Intrinsic analysis on manifolds -- Landmark-based shape spaces -- Kendall's similarity shape spaces [characters omitted] -- The planar shape space [characters omitted] -- Reflection similarity shape spaces R[characters omitted] -- Stiefel manifolds V[characters omitted] -- Affine shape spaces A[characters omitted] -- Real projective spaces and projective shape spaces -- Nonparametric Bayes inference on manifolds -- Nonparametric Bayes regression, classification and hypothesis testing on manifolds -- Appendixes: A. Differentiable manifolds -- B. Riemannian manifolds -- C. Dirichlet processes -- D. Parametric models on S[character omitted] and [characters omitted].
    Additional Edition: Print version: ISBN 9781107019584
    Language: English
    Library Location Call Number Volume/Issue/Year Availability
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  • 4
    Online Resource
    Online Resource
    Cambridge ; : Cambridge University Press,
    UID:
    edocfu_9959245783602883
    Format: 1 online resource (xiii, 237 pages) : , digital, PDF file(s).
    Edition: 1st ed.
    ISBN: 1-107-23115-9 , 1-280-39417-X , 9786613572097 , 1-139-33789-0 , 1-139-09476-9 , 1-139-34034-4 , 1-139-34192-8 , 1-139-33702-5 , 1-139-33876-5
    Series Statement: Institute of Mathematical Statistics monographs
    Content: 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.
    Note: Title from publisher's bibliographic system (viewed on 05 Oct 2015). , Introduction -- Examples -- Location and spread on metric spaces -- Extrinsic analysis on manifolds -- Intrinsic analysis on manifolds -- Landmark-based shape spaces -- Kendall's similarity shape spaces [characters omitted] -- The planar shape space [characters omitted] -- Reflection similarity shape spaces R[characters omitted] -- Stiefel manifolds V[characters omitted] -- Affine shape spaces A[characters omitted] -- Real projective spaces and projective shape spaces -- Nonparametric Bayes inference on manifolds -- Nonparametric Bayes regression, classification and hypothesis testing on manifolds -- Appendixes: A. Differentiable manifolds -- B. Riemannian manifolds -- C. Dirichlet processes -- D. Parametric models on S[character omitted] and [characters omitted]. , English
    Additional Edition: ISBN 1-107-48431-6
    Additional Edition: ISBN 1-107-01958-3
    Language: English
    Library Location Call Number Volume/Issue/Year Availability
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