Geostatistical Functional Data Analysis (eBook)

Jorge Mateu is Full Professor of Statistics at the Department of Mathematics of University Jaume I of Castellon. His research focuses on stochastic processes with a particular interest in spatial and spatio-temporal point processes and geostatistics. Ramón Giraldo is Full Professor of Statistics at the Department of Statistics at the Universidad Nacional de Colombia. His research focuses on non-parametric statistics, functional data analysis, and spatial and spatio-temporal geostatistics.

Preface

1. Introduction to Geostatistical Functional Data Analysis

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

7. Clustering spatial functional data

8. Nonparametric statistical analysis of spatially distributed functional data

9. A non parametric algorithm for spatially dependent functional data: Bagging Voronoi for clustering,
dimensional reduction and regression

10. Non-parametric inference for spatio-temporal data based on local null hypothesis testing for functional data

11. A penalized regression model for spatial functional data with application to the analysis of the production of waste in Venice province

12. Quasi-Maximum Likelihood Estimators for Functional Linear Spatial Autoregressive Models

13. Spatial Prediction and Optimal Sampling for Multivariate Functional Random Fields

14. Spatio-temporal Functional Data Analysis

15. A comparison of spatio-temporal and functional kriging approaches

16. From spatio-temporal smoothing to functional spatial regression: a penalized approach

Index