Complex Data Modeling and Computationally Intensive Statistical Methods
The last years have seen the advent and development of many devices able to record and store an always increasing amount of complex and high dimensional data; 3D images generated by medical scanners or satellite remote sensing, DNA microarrays, real time
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Pietro Mantovan Piercesare Secchi Editors
Complex Data Modeling and Computationally Intensive Statistical Methods
123
Physica-Verlag A Springer Company
Pietro Mantovan Piercesare Secchi Complex Data Modeling and Computationally Intensive Statistical Methods
Contributions to Statistics
For further volumes: http://www.springer.com/series/2912
Pietro Mantovan (Editor) Piercesare Secchi (Editor)
Complex Data Modeling and Computationally Intensive Statistical Methods
Physica-Verlag A Springer Company
Pietro Mantovan Ca’ Foscari University of Venice Venice, Italy
Piercesare Secchi Politecnico di Milano Milan, Italy
ISBN 978-88-470-1385-8
e-ISBN 978-88-470-1386-5
DOI 10.1007/978-88-470-1386-5
Library of Congress Control Number: 2010929480
Springer Milan Dordrecht Heidelberg London New York
Jointly published with Physica-Verlag Heidelberg, Germany © Springer-Verlag Italia 2010
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Preface
Recent years have seen the advent and development of many devices able to record and store an ever increasing amount of information. The fast progress of these technologies is ubiquitous throughout all fields of science and applied contexts, ranging from medicine, biology and life sciences, to economics and industry. The data provided by these instruments have different forms: 2D-3D images generated by diagnostic medical scanners, computer vision or satellite remote sensing, microarray data and gene sets, integrated clinical and administrative data from public health databases, real time monitoring data of a bio-marker, system control datasets. All these data share the common characteristic of being complex and often highly dimensional. The analysis of complex and highly dimensional data poses new challenges to the statistician and requires the development of novel models and techniques, fueling many fascinating and fast growing research areas of modern statistics. An incomplete
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