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Geostatistical Functional Data Analysis
Geostatistical Functional Data Analysis Explore the intersection between geostatistics and functional data analysis with this insightful new reference 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 correlate...
Complex Stochastic Systems
Complex stochastic systems comprises a vast area of research, from modelling specific applications to model fitting, estimation procedures, and computing issues. The exponential growth in computing power over the last two decades has revolutionized statistical analysis and led to rapid developments and great progress in this emerging field. In Complex Stochastic Systems, leading researchers address various statistical aspects of the field, illustrated by some very concrete applications. A Primer on Markov Chain Monte Carlo by Peter J. Green provides a wide-ranging mixture of the mathematical and statistical ideas, enriched with concrete examples and more than 100 references. Causal Inference...
Spatial and Spatio-Temporal Geostatistical Modeling and Kriging
Statistical Methods for Spatial and Spatio-Temporal Data Analysis provides a complete range of spatio-temporal covariance functions and discusses ways of constructing them. This book is a unified approach to modeling spatial and spatio-temporal data together with significant developments in statistical methodology with applications in R. This book includes: Methods for selecting valid covariance functions from the empirical counterparts that overcome the existing limitations of the traditional methods. The most innovative developments in the different steps of the kriging process. An up-to-date account of strategies for dealing with data evolving in space and time. An accompanying website featuring R code and examples
Spatial Point Process Modelling and Its Applications
Este libro de proceedings se edita para ponerlo a disposición de los asistentes a la Internacional Conference on Spatial Pont Process Modelling and its Applications (SPPA), realizada en Benicàssim en abril de 2004.
Mathematics of Planet Earth
It is widely recognized that the degree of development of a science is given by the transition from a mainly descriptive stage to a more quantitative stage. In this transition, qualitative interpretations (conceptual models) are complemented with quantification (numerical models, both, deterministic and stochastic). This has been the main task of mathematical geoscientists during the last forty years - to establish new frontiers and new challenges in the study and understanding of the natural world. Mathematics of Planet Earth comprises the proceedings of the International Association for Mathematical Geosciences Conference (IAMG2013), held in Madrid from September 2-6, 2013. The Conference addresses researchers, professionals and students. The proceedings contain more than 150 original contributions and give a multidisciplinary vision of mathematical geosciences.
Recent Advances in Functional Data Analysis and Related Topics
New technologies allow us to handle increasingly large datasets, while monitoring devices are becoming ever more sophisticated. This high-tech progress produces statistical units sampled over finer and finer grids. As the measurement points become closer, the data can be considered as observations varying over a continuum. This intrinsic continuous data (called functional data) can be found in various fields of science, including biomechanics, chemometrics, econometrics, environmetrics, geophysics, medicine, etc. The failure of standard multivariate statistics to analyze such functional data has led the statistical community to develop appropriate statistical methodologies, called Functional...
Spatial Data Science
Spatial Data Science introduces fundamental aspects of spatial data that every data scientist should know before they start working with spatial data. These aspects include how geometries are represented, coordinate reference systems (projections, datums), the fact that the Earth is round and its consequences for analysis, and how attributes of geometries can relate to geometries. In the second part of the book, these concepts are illustrated with data science examples using the R language. In the third part, statistical modelling approaches are demonstrated using real world data examples. After reading this book, the reader will be well equipped to avoid a number of major spatial data analy...
Classification and Data Mining
This volume contains both methodological papers showing new original methods, and papers on applications illustrating how new domain-specific knowledge can be made available from data by clever use of data analysis methods. The volume is subdivided in three parts: Classification and Data Analysis; Data Mining; and Applications. The selection of peer reviewed papers had been presented at a meeting of classification societies held in Florence, Italy, in the area of "Classification and Data Mining".
TransMath
The book "TransMath - Innovative Solutions from Mathematical Technology" has been conceived as a tool for the dissemination of scientific knowledge. This publication is addressed to those companies with innovation needs that could be met through mathematical technology. The book maps both existing and possible interactions and connections that enable technology transfer between Spanish mathematical research and industrial and business sectors. Businesses can determine the level of implementation and demand for such technology within their sector and understand the benefits and innovations achieved in other companies and industries with the application of mathematical techniques. The information is classified into eleven sectors of economic activity: Biomedicine & Health; Construction; Economics & Finance; Energy & Environment; Food; ICT; Logistics & Transport; Management & Tourism; Metal & Machinery; Public Administration; and Technical Services.
