Geostatistical Functional Data Analysis (Wiley Series in Probability and Statistics) 1st Edition Jorge Mateu (Editor)

Geostatistical Functional Data Analysis (Wiley Series in Probability and Statistics) – Ebook Instant Download/Delivery ISBN(s): 9781119387848,1119387841

Product details:

• ISBN-10 ‏ : ‎ 1119387841
• ISBN-13 ‏ : ‎ 978-1119387848
• Author(s): Jorge Mateu, Ramon Giraldo

Geostatistical Functional Data Analysis presents a unified approach to modelling functional data when spatial and spatio-temporal correlations are present. The Editors link together the wide research areas of geostatistics and functional data analysis to provide the reader with a new area called geostatistical functional data analysis that will bring new insights and new open questions to researchers coming from both scientific fields. This book provides a complete and up-to-date account to deal with functional data that is spatially correlated, but also includes the most innovative developments in different open avenues in this field.

Containing contributions from leading experts in the field, this practical guide provides readers with the necessary tools to employ and adapt classic statistical techniques to handle spatial regression.

Table contents:

1 Introduction to Geostatistical Functional Data Analysis

Part I Mathematical and Statistical Foundations 27

2 Mathematical Foundations of Functional Kriging in Hilbert Spaces and Riemannian Manifolds

3 Universal, Residual, and External Drift Functional Kriging

4 Extending Functional Kriging When Data Are Multivariate Curves: Some Technical Considerations and Operational Solutions

5 Geostatistical Analysis in Bayes Spaces: Probability Densities and Compositional Data

6 Spatial Functional Data Analysis for Probability Density Functions: Compositional Functional Data vs. Distributional Data Approach

Part II Statistical Techniques for Spatially Correlated Functional Data 155

7 Clustering Spatial Functional Data

8 Nonparametric Statistical Analysis of Spatially Distributed Functional Data

9 A Nonparametric Algorithm for Spatially Dependent Functional Data: Bagging Voronoi for Clustering, Dimensional Reduction, and Regression

10 Nonparametric Inference for Spatiotemporal Data Based on Local Null Hypothesis Testing for Functional Data

11 Modeling Spatially Dependent Functional Data by Spatial Regression with Differential Regularization

12 Quasi-maximum Likelihood Estimators for Functional Linear Spatial Autoregressive Models

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