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Modern Statistical Methods for Spatial and Multivariate Data (STEAM-H: Science, Technology, Engineering, Agriculture, Mathematics & Health) - Hardcover
Synopsis
This contributed volume features invited papers on current models and statistical methods for spatial and multivariate data. With a focus on recent advances in statistics, topics include spatio-temporal aspects, classification techniques, the multivariate outcomes with zero and doubly-inflated data, discrete choice modelling, copula distributions, and feasible algorithmic solutions. Special emphasis is placed on applications such as the use of spatial and spatio-temporal models for rainfall in South Carolina and the multivariate sparse areal mixed model for the Census dataset for the state of Iowa. Articles use simulated and aggregated data examples to show the flexibility and wide applications of proposed techniques.
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From the Back Cover
This contributed volume features invited papers on current models and statistical methods for spatial and multivariate data. With a focus on recent advances in statistics, topics include spatio-temporal aspects, classification techniques, the multivariate outcomes with zero and doubly-inflated data, discrete choice modelling, copula distributions, and feasible algorithmic solutions. Special emphasis is placed on applications such as the use of spatial and spatio-temporal models for rainfall in South Carolina and the multivariate sparse areal mixed model for the Census dataset for the state of Iowa. Articles use simulated and aggregated data examples to show the flexibility and wide applications of proposed techniques.
Carefully peer-reviewed and pedagogically presented for a broad readership, this volume is suitable for graduate and postdoctoral students interested in interdisciplinary research. Researchers in applied statistics and sciences will find this book an important resource on the latest developments in the field. In keeping with the STEAM-H series, the editors hope to inspire interdisciplinary understanding and collaboration.
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- PublisherSpringer
- Publication date2019
- ISBN 10 3030114309
- ISBN 13 9783030114305
- BindingHardcover
- LanguageEnglish
- Edition number1
- Number of pages191
- EditorDiawara Norou
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Modern Statistical Methods for Spatial and Multivariate Data.
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XIV, 177 p. Hardcover. Versand aus Deutschland / We dispatch from Germany via Air Mail. Einband bestoßen, daher Mängelexemplar gestempelt, sonst sehr guter Zustand. Imperfect copy due to slightly bumped cover, apart from this in very good condition. Stamped. STEAM-H: Science, Technology, Engineering, Agriculture, Mathematics & Health. Sprache: Englisch. Seller Inventory # 9635GB
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Modern Statistical Methods for Spatial and Multivariate Data (STEAM-H: Science, Technology, Engineering, Agriculture, Mathematics & Health)
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Modern Statistical Methods for Spatial and Multivariate Data
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Springer International Publishing, 2019
ISBN 10: 3030114309
ISBN 13: 9783030114305
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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Exposes new research directions and solutions in spatio-temporal and multivariate dataIncreases understanding of models in medical and engineering areasFeatures recent advances in spatio-temporal aspects, classification techniques. Seller Inventory # 258911330
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Modern Statistical Methods for Spatial and Multivariate Data
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ISBN 10: 3030114309
ISBN 13: 9783030114305
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Buch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This contributed volume features invited papers on current models and statistical methods for spatial and multivariate data. With a focus on recent advances in statistics, topics include spatio-temporal aspects, classification techniques, the multivariate outcomes with zero and doubly-inflated data, discrete choice modelling, copula distributions, and feasible algorithmic solutions. Special emphasis is placed on applications such as the use of spatial and spatio-temporal models for rainfall in South Carolina and the multivariate sparse areal mixed model for the Census dataset for the state of Iowa. Articles use simulated and aggregated data examples to show the flexibility and wide applications of proposed techniques. Carefully peer-reviewed and pedagogically presented for a broad readership, this volume is suitable for graduate and postdoctoral students interested in interdisciplinary research. Researchers in applied statistics and sciences will find this book an important resource on the latest developments in the field. In keeping with the STEAM-H series, the editors hope to inspire interdisciplinary understanding and collaboration. 192 pp. Englisch. Seller Inventory # 9783030114305
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Modern Statistical Methods for Spatial and Multivariate Data
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ISBN 10: 3030114309
ISBN 13: 9783030114305
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Buch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - This contributed volume features invited papers on current models and statistical methods for spatial and multivariate data. With a focus on recent advances in statistics, topics include spatio-temporal aspects, classification techniques, the multivariate outcomes with zero and doubly-inflated data, discrete choice modelling, copula distributions, and feasible algorithmic solutions. Special emphasis is placed on applications such as the use of spatial and spatio-temporal models for rainfall in South Carolina and the multivariate sparse areal mixed model for the Census dataset for the state of Iowa. Articles use simulated and aggregated data examples to show the flexibility and wide applications of proposed techniques.Carefully peer-reviewed and pedagogically presented for a broad readership, this volume is suitable for graduate and postdoctoral students interested in interdisciplinary research. Researchers in applied statistics and sciences will find thisbook an important resource on the latest developments in the field. In keeping with the STEAM-H series, the editors hope to inspire interdisciplinary understanding and collaboration. Seller Inventory # 9783030114305
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Modern Statistical Methods for Spatial and Multivariate Data (STEAM-H: Science, Technology, Engineering, Agriculture, Mathematics & Health)
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