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Modern Methodology and Applications in Spatial-Temporal Modeling

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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.

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Detail Information

Series Title

SpringerBriefs in Statistics

Call Number

-

Publisher

: ., 2015

Collation

XV

Language

English

ISBN/ISSN

978-4-431-55338-0

Classification

NONE

Content Type

-

Media Type

-

Carrier Type

-

Edition

1

Subject(s)

Computer Science
Physics
Statistical Theory and Methods
Statistics and Computing
Statistics in Engineering
Chemistry and Earth Sciences

Specific Detail Info

-

Statement of Responsibility

SpringerBriefs in Statistics

Other Information

Cataloger

ULAN

Source

-

Validator

Taufik

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