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Parametric Nonparametric Inference Statistical by Brombin Chiara (18 results)
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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
Seller rating 5 out of 5 stars
Paperback. Condition: New. 1st ed. 2016.
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Parametric and Nonparametric Inference for Statistical Dynamic Shape Analysis with Applications (SpringerBriefs in Statistics)
Seller: Ria Christie Collections, Uxbridge, United Kingdom
Seller rating 5 out of 5 stars
£ 47.99
£ 11.98 shipping
Ships from United Kingdom to U.S.A.Quantity: Over 20 available
Add to basketCondition: New. In.
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Parametric and Nonparametric Inference for Statistical Dynamic Shape Analysis With Applications
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
Seller rating 5 out of 5 stars
Condition: New.
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Parametric and Nonparametric Inference for Statistical Dynamic Shape Analysis With Applications
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
Seller rating 5 out of 5 stars
Condition: As New. Unread book in perfect condition.
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Paperback. Condition: Brand New. 128 pages. 9.00x6.00x0.50 inches. In Stock.
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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
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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Parametric and Nonparametric Inference for Statistical Dynamic Shape Analysis with Applications
Language: English
Published by Springer International Publishing, Springer International Publishing Feb 2016, 2016
ISBN 10: 3319263102 ISBN 13: 9783319263106
Seller: buchversandmimpf2000, Emtmannsberg, BAYE, Germany
Seller rating 5 out of 5 stars
Taschenbuch. Condition: Neu. 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 GmbH, Tiergartenstr. 17, 69121 Heidelberg 128 pp. Englisch.
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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
Paperback. Condition: New. 1st ed. 2016.
-
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. 110.
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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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Taschenbuch. Condition: Neu. Parametric and Nonparametric Inference for Statistical Dynamic Shape Analysis with Applications | Chiara Brombin (u. a.) | Taschenbuch | 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 Print on Demand.
