Name: Modern Methodology and Applications in Spatial-Temporal Modeling (en Inglés)
SKU: 49228118
Price: 54.12 USD
Availability: InStock
Author: Peters, Gareth William ; Matsui, Tomoko

portada Modern Methodology and Applications in Spatial-Temporal Modeling (en Inglés)

Modern Methodology and Applications in Spatial-Temporal Modeling (en Inglés)

Formato

Libro Físico

Editorial

Springer

Autor

Peters, Gareth William ; Matsui, Tomoko

Año

2016

Idioma

Inglés

N° páginas

111

Encuadernación

Tapa Blanda

ISBN13

9784431553380

N° edición

Categorías

Probabilidad y estadística
Software de matemáticas y estadísticas

Modern Methodology and Applications in Spatial-Temporal Modeling (en Inglés)

Peters, Gareth William ; Matsui, Tomoko (Autor) · Springer · Tapa Blanda

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Reseña del libro "Modern Methodology and Applications in Spatial-Temporal Modeling (en Inglés)"

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.