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Permutation Tests in Shape Analysis (Springer Briefs in Statistics (15))
Seller: Zubal-Books, Since 1961, Cleveland, OH, U.S.A.
Seller rating 5 out of 5 stars
Condition: New. *Price HAS BEEN REDUCED by 10% until Tuesday, May 26 (holiday SALE item)* 105 pp., Paperback, new. - If you are reading this, this item is actually (physically) in our stock and ready for shipment once ordered. We are not bookjackers. Buyer is responsible for any additional duties, taxes, or fees required by recipient's country.
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Condition: As New. Unread book in perfect condition.
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Parametric and Nonparametric Inference for Statistical Dynamic Shape Analysis with Applications
Language: English
Published by Springer International Publishing AG, CH, 2016
ISBN 10: 3319263102 ISBN 13: 9783319263106
Seller: Rarewaves.com USA, London, LONDO, United Kingdom
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Permutation Tests in Shape Analysis (SpringerBriefs in Statistics, 15)
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Parametric and Nonparametric Inference for Statistical Dynamic Shape Analysis with Applications (SpringerBriefs in Statistics)
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Parametric and Nonparametric Inference for Statistical Dynamic Shape Analysis With Applications
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Condition: New. pp. 108.
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Parametric and Nonparametric Inference for Statistical Dynamic Shape Analysis With Applications
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Add to basketPaperback. Condition: Brand New. 1st edition. 95 pages. 9.00x6.00x0.25 inches. In Stock.
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Parametric and Nonparametric Inference for Statistical Dynamic Shape Analysis with Applications
Language: English
Published by Springer, Palgrave Macmillan, 2016
ISBN 10: 3319263102 ISBN 13: 9783319263106
Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book considers specific inferential issues arising from the analysis of dynamic shapes with the attempt to solve the problems at hand using probability models and nonparametric tests. The models are simple to understand and interpret and provide a useful tool to describe the global dynamics of the landmark configurations. However, because of the non-Euclidean nature of shape spaces, distributions in shape spaces are not straightforward to obtain. The book explores the use of the Gaussian distribution in the configuration space, with similarity transformations integrated out. Specifically, it works with the offset-normal shape distribution as a probability model for statistical inference on a sample of a temporal sequence of landmark configurations. This enables inference for Gaussian processes from configurations onto the shape space. The book is divided in two parts, with the first three chapters covering material on the offset-normal shape distribution, and the remaining chapters covering the theory of NonParametric Combination (NPC) tests. The chapters offer a collection of applications which are bound together by the theme of this book. They refer to the analysis of data from the FG-NET (Face and Gesture Recognition Research Network) database with facial expressions. For these data, it may be desirable to provide a description of the dynamics of the expressions, or testing whether there is a difference between the dynamics of two facial expressions or testing which of the landmarks are more informative in explaining the pattern of an expression.
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Taschenbuch. Condition: Neu. Parametric and Nonparametric Inference for Statistical Dynamic Shape Analysis with Applications | Chiara Brombin (u. a.) | Taschenbuch | SpringerBriefs in Statistics | x | Englisch | 2016 | Springer | EAN 9783319263106 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
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Condition: Sehr gut. Zustand: Sehr gut | Sprache: Englisch | Produktart: Bücher | Statistical shape analysis is a geometrical analysis from a set of shapes in which statistics are measured to describe geometrical properties from similar shapes or different groups, for instance, the difference between male and female Gorilla skull shapes, normal and pathological bone shapes, etc. Some of the important aspects of shape analysis are to obtain a measure of distance between shapes, to estimate average shapes from a (possibly random) sample and to estimate shape variability in a sample[1]. One of the main methods used is principal component analysis. Specific applications of shape analysis may be found in archaeology, architecture, biology, geography, geology, agriculture, genetics, medical imaging, security applications such as face recognition, entertainment industry (movies, games), computer-aided design and manufacturing. This is a proposal for a new Brief on statistical shape analysis and the various new parametric and non-parametric methods utilized to facilitate shape analysis. ż ż.
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Parametric and Nonparametric Inference for Statistical Dynamic Shape Analysis with Applications
Language: English
Published by Springer International Publishing AG, CH, 2016
ISBN 10: 3319263102 ISBN 13: 9783319263106
US$ 69.53
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Condition: new. Questo è un articolo print on demand.
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Permutation Tests in Shape Analysis
Language: English
Published by Springer New York Sep 2013, 2013
ISBN 10: 1461481627 ISBN 13: 9781461481621
Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
Seller rating 5 out of 5 stars
Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Statistical shape analysis is a geometrical analysis from a set of shapes in which statistics are measured to describe geometrical properties from similar shapes or different groups, for instance, the difference between male and female Gorilla skull shapes, normal and pathological bone shapes, etc. Some of the important aspects of shape analysis are to obtain a measure of distance between shapes, to estimate average shapes from a (possibly random) sample and to estimate shape variability in a sample[1]. One of the main methods used is principal component analysis. Specific applications of shape analysis may be found in archaeology, architecture, biology, geography, geology, agriculture, genetics, medical imaging, security applications such as face recognition, entertainment industry (movies, games), computer-aided design and manufacturing. This is a proposal for a new Brief on statistical shape analysis and the various new parametric and non-parametric methods utilized to facilitate shape analysis. 108 pp. Englisch.
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Parametric and Nonparametric Inference for Statistical Dynamic Shape Analysis with Applications
Language: English
Published by Springer International Publishing Feb 2016, 2016
ISBN 10: 3319263102 ISBN 13: 9783319263106
Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
Seller rating 5 out of 5 stars
Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book considers specific inferential issues arising from the analysis of dynamic shapes with the attempt to solve the problems at hand using probability models and nonparametric tests. The models are simple to understand and interpret and provide a useful tool to describe the global dynamics of the landmark configurations. However, because of the non-Euclidean nature of shape spaces, distributions in shape spaces are not straightforward to obtain. The book explores the use of the Gaussian distribution in the configuration space, with similarity transformations integrated out. Specifically, it works with the offset-normal shape distribution as a probability model for statistical inference on a sample of a temporal sequence of landmark configurations. This enables inference for Gaussian processes from configurations onto the shape space. The book is divided in two parts, with the first three chapters covering material on the offset-normal shape distribution, and the remaining chapters covering the theory of NonParametric Combination (NPC) tests. The chapters offer a collection of applications which are bound together by the theme of this book. They refer to the analysis of data from the FG-NET (Face and Gesture Recognition Research Network) database with facial expressions. For these data, it may be desirable to provide a description of the dynamics of the expressions, or testing whether there is a difference between the dynamics of two facial expressions or testing which of the landmarks are more informative in explaining the pattern of an expression. 128 pp. Englisch.
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Condition: New. Print on Demand pp. 108.
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Condition: New. Print on Demand pp. 110.
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Condition: New. PRINT ON DEMAND pp. 108.
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Condition: New. PRINT ON DEMAND pp. 110.
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Parametric and Nonparametric Inference for Statistical Dynamic Shape Analysis with Applications
Language: English
Published by Springer International Publishing, 2016
ISBN 10: 3319263102 ISBN 13: 9783319263106
Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Explores specific inferential issues arising from the analysis of dynamic shapes with the attempt to solve the problems at hand using probability models and nonparametric testsUses the Expectation Maximization (EM) algori.
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Parametric and Nonparametric Inference for Statistical Dynamic Shape Analysis with Applications
Language: English
Published by Springer, Palgrave Macmillan Feb 2016, 2016
ISBN 10: 3319263102 ISBN 13: 9783319263106
Seller: buchversandmimpf2000, Emtmannsberg, BAYE, Germany
Seller rating 5 out of 5 stars
Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book considers specific inferential issues arising from the analysis of dynamic shapes with the attempt to solve the problems at hand using probability models and nonparametric tests. The models are simple to understand and interpret and provide a useful tool to describe the global dynamics of the landmark configurations. However, because of the non-Euclidean nature of shape spaces, distributions in shape spaces are not straightforward to obtain.The book explores the use of the Gaussian distribution in the configuration space, with similarity transformations integrated out.Specifically, it works with the offset-normal shape distribution as a probability model for statistical inference on a sample of a temporal sequence of landmark configurations. This enables inference for Gaussian processes from configurations onto the shape space. The book is divided in two parts, with the first three chapters covering material on the offset-normal shape distribution, and the remaining chapters covering the theory of NonParametric Combination (NPC) tests. The chapters offer a collection of applications which are bound together by the theme of this book.They refer to the analysis of data from the FG-NET (Face and Gesture RecognitionResearch Network) database with facial expressions. For these data, it may be desirable to provide a description of the dynamics of the expressions, or testing whether there is a difference between the dynamics of two facialexpressions or testing which of the landmarks are more informative in explaining thepattern of an expression.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 128 pp. Englisch.
