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Geostatistical Functional Data Analysis (Wiley Series in Probability and Statistics) (en Inglés)
Jorge Mateu Mahiques; Ramon Giraldo (Autor)
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Geostatistical Functional Data Analysis (Wiley Series in Probability and Statistics) (en Inglés) - Jorge Mateu Mahiques; Ramon Giraldo
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Origen: Estados Unidos
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Reseña del libro "Geostatistical Functional Data Analysis (Wiley Series in Probability and Statistics) (en Inglés)"
This book presents a unified approach to modelling functional data when spatial and spatio-temporal correlations are present. The editors link together for the first time 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. Leading experts in the field, the Editors have put together a collection of chapters covering state-of-the-art methods in this area. The individual chapters combine formal statements of the results including mathematical proofs with informal and naive statements of classical and new results.This book serves the scientific community to know what has been done so far, and to know what type of open questions need of future answers. After an introduction and brief overview, the book includes the following: A detailed exposition of the spatial kriging methodology when dealing with functions. A detailed exposition of more classical statistical techniques already adapted to the functional case and now extended in the right way to handle spatial correlations. Learning ANOVA, regression, clustering methods is crucial for a correct use of the statistical methods when the spatial correlation is present among a collection of curves sampled in a region. A thorough guide to understanding similarities and differences between spatio-temporal data analysis and functional data analysis. The reader will be guided in terms of modelling and computational issues. The information here allows the reader not only to fully understand kriging methods, but to use the most innovative functional methods adapted to spatially correlated functions, to deal with spatio-temporal datasets from a functional perspective, and to being able to handle massive databases from a more computational perspective. This book provides a complete an 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.
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