Items related to Modern Methodology and Applications in Spatial-Temporal...
Modern Methodology and Applications in Spatial-Temporal Modeling (SpringerBriefs in Statistics) - Softcover
Synopsis
This book provides a modern introductory tutorial on specialized methodological and applied aspects of spatial and temporal modeling. The areas covered involve a range of topics which reflect the diversity of this domain of research across a number of quantitative disciplines. For instance, the first chapter deals with non-parametric Bayesian inference via a recently developed framework known as kernel mean embedding which has had a significant influence in machine learning disciplines. The second chapter takes up non-parametric statistical methods for spatial field reconstruction and exceedance probability estimation based on Gaussian process-based models in the context of wireless sensor network data. The third chapter presents signal-processing methods applied to acoustic mood analysis based on music signal analysis. The fourth chapter covers models that are applicable to time series modeling in the domain of speech and language processing. This includes aspects of factor analysis, independent component analysis in an unsupervised learning setting. The chapter moves on to include more advanced topics on generalized latent variable topic models based on hierarchical Dirichlet processes which recently have been developed in non-parametric Bayesian literature. The final chapter discusses aspects of dependence modeling, primarily focusing on the role of extreme tail-dependence modeling, copulas, and their role in wireless communications system models.
"synopsis" may belong to another edition of this title.
Search results for Modern Methodology and Applications in Spatial-Temporal...
Seller Image
Modern Methodology and Applications in Spatial-Temporal Modeling
Published by
Springer Japan Jan 2016, 2016
ISBN 10: 443155338X
ISBN 13: 9784431553380
New
Taschenbuch
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 provides a modern introductory tutorial on specialized methodological and applied aspects of spatial and temporal modeling. The areas covered involve a range of topics which reflect the diversity of this domain of research across a number of quantitative disciplines. For instance, the first chapter deals with non-parametric Bayesian inference via a recently developed framework known as kernel mean embedding which has had a significant influence in machine learning disciplines. The second chapter takes up non-parametric statistical methods for spatial field reconstruction and exceedance probability estimation based on Gaussian process-based models in the context of wireless sensor network data. The third chapter presents signal-processing methods applied to acoustic mood analysis based on music signal analysis. The fourth chapter covers models that are applicable to time series modeling in the domain of speech and language processing. This includes aspects of factor analysis, independent component analysis in an unsupervised learning setting. The chapter moves on to include more advanced topics on generalized latent variable topic models based on hierarchical Dirichlet processes which recently have been developed in non-parametric Bayesian literature. The final chapter discusses aspects of dependence modeling, primarily focusing on the role of extreme tail-dependence modeling, copulas, and their role in wireless communications system models. 128 pp. Englisch. Seller Inventory # 9784431553380
Quantity: 2 available
Stock Image
Modern Methodology and Applications in Spatial-Temporal Modeling (SpringerBriefs in Statistics / JSS Research Series in Statistics)
Seller: Books Puddle, New York, NY, U.S.A.
Seller rating 4 out of 5 stars
Condition: New. 125. Seller Inventory # 26372160738
Quantity: 4 available
Stock Image
Modern Methodology and Applications in Spatial-Temporal Modeling (SpringerBriefs in Statistics / JSS Research Series in Statistics)
Print on DemandSeller: Majestic Books, Hounslow, United Kingdom
Seller rating 5 out of 5 stars
Condition: New. Print on Demand 125. Seller Inventory # 374933309
Quantity: 4 available
Stock Image
Modern Methodology and Applications in Spatial-Temporal Modeling (SpringerBriefs in Statistics / JSS Research Series in Statistics)
Print on DemandSeller: Biblios, Frankfurt am main, HESSE, Germany
Seller rating 5 out of 5 stars
Condition: New. PRINT ON DEMAND 125. Seller Inventory # 18372160744
Quantity: 4 available
Seller Image
Modern Methodology and Applications in Spatial-Temporal Modeling
Published by
Springer Japan, 2016
ISBN 10: 443155338X
ISBN 13: 9784431553380
New
Kartoniert / Broschiert
Seller: moluna, Greven, Germany
Seller rating 5 out of 5 stars
Kartoniert / Broschiert. Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Covers specialized topics in spatial-temporal modeling provided by world experts for an introduction to key componentsDiscusses a rigorous probabilistic and statistical framework for a range of contemporary topics of importance to a diverse number. Seller Inventory # 31408266
Quantity: Over 20 available
Seller Image
Modern Methodology and Applications in Spatial-Temporal Modeling
Published by
Springer Japan, Springer Japan Jan 2016, 2016
ISBN 10: 443155338X
ISBN 13: 9784431553380
New
Taschenbuch
Seller: buchversandmimpf2000, Emtmannsberg, BAYE, Germany
Seller rating 5 out of 5 stars
Taschenbuch. Condition: Neu. Neuware -¿This book provides a modern introductory tutorial on specialized methodological and applied aspects of spatial and temporal modeling. The areas covered involve a range of topics which reflect the diversity of this domain of research across a number of quantitative disciplines. For instance, the first chapter deals with non-parametric Bayesian inference via a recently developed framework known as kernel mean embedding which has had a significant influence in machine learning disciplines. The second chapter takes up non-parametric statistical methods for spatial field reconstruction and exceedance probability estimation based on Gaussian process-based models in the context of wireless sensor network data. The third chapter presents signal-processing methods applied to acoustic mood analysis based on music signal analysis. The fourth chapter covers models that are applicable to time series modeling in the domain of speech and language processing. This includes aspects of factor analysis, independent component analysis in an unsupervised learning setting. The chapter moves on to include more advanced topics on generalized latent variable topic models based on hierarchical Dirichlet processes which recently have been developed in non-parametric Bayesian literature. The final chapter discusses aspects of dependence modeling, primarily focusing on the role of extreme tail-dependence modeling, copulas, and their role in wireless communications system models.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 128 pp. Englisch. Seller Inventory # 9784431553380
Quantity: 2 available
Stock Image
Modern Methodology and Applications in Spatial-temporal Modeling
Seller: Revaluation Books, Exeter, United Kingdom
Seller rating 5 out of 5 stars
Paperback. Condition: Brand New. 125 pages. 9.00x6.00x0.50 inches. In Stock. Seller Inventory # zk443155338X
Quantity: 1 available
Seller Image
Modern Methodology and Applications in Spatial-Temporal Modeling
Published by
Springer Japan, Springer Japan, 2016
ISBN 10: 443155338X
ISBN 13: 9784431553380
New
Taschenbuch
Seller: AHA-BUCH GmbH, Einbeck, Germany
Seller rating 5 out of 5 stars
Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book provides a modern introductory tutorial on specialized methodological and applied aspects of spatial and temporal modeling. The areas covered involve a range of topics which reflect the diversity of this domain of research across a number of quantitative disciplines. For instance, the first chapter deals with non-parametric Bayesian inference via a recently developed framework known as kernel mean embedding which has had a significant influence in machine learning disciplines. The second chapter takes up non-parametric statistical methods for spatial field reconstruction and exceedance probability estimation based on Gaussian process-based models in the context of wireless sensor network data. The third chapter presents signal-processing methods applied to acoustic mood analysis based on music signal analysis. The fourth chapter covers models that are applicable to time series modeling in the domain of speech and language processing. This includes aspects of factor analysis, independent component analysis in an unsupervised learning setting. The chapter moves on to include more advanced topics on generalized latent variable topic models based on hierarchical Dirichlet processes which recently have been developed in non-parametric Bayesian literature. The final chapter discusses aspects of dependence modeling, primarily focusing on the role of extreme tail-dependence modeling, copulas, and their role in wireless communications system models. Seller Inventory # 9784431553380
Quantity: 1 available