Overview
- Exposes new research directions and solutions in spatio-temporal and multivariate data
- Increases understanding of models in medical and engineering areas
- Features recent advances in spatio-temporal aspects, classification techniques, the multivariate outcomes with zero and doubly-inflated data, discrete choice modelling, kernel functions of support matrix machines and copula distributions
Part of the book series: STEAM-H: Science, Technology, Engineering, Agriculture, Mathematics & Health (STEAM)
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Table of contents (9 chapters)
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Front Matter
Keywords
About this book
Carefully peer-reviewed and pedagogically presented for a broad readership, this volume is suitable for graduate and postdoctoral students interested in interdisciplinary research. Researchers in applied statistics and sciences will find thisbook an important resource on the latest developments in the field. In keeping with the STEAM-H series, the editors hope to inspire interdisciplinary understanding and collaboration.
Editors and Affiliations
Bibliographic Information
Book Title: Modern Statistical Methods for Spatial and Multivariate Data
Editors: Norou Diawara
Series Title: STEAM-H: Science, Technology, Engineering, Agriculture, Mathematics & Health
DOI: https://doi.org/10.1007/978-3-030-11431-2
Publisher: Springer Cham
eBook Packages: Mathematics and Statistics, Mathematics and Statistics (R0)
Copyright Information: Springer Nature Switzerland AG 2019
Hardcover ISBN: 978-3-030-11430-5Published: 11 July 2019
eBook ISBN: 978-3-030-11431-2Published: 29 June 2019
Series ISSN: 2520-193X
Series E-ISSN: 2520-1948
Edition Number: 1
Number of Pages: XIV, 177
Number of Illustrations: 13 b/w illustrations, 25 illustrations in colour
Topics: Applications of Mathematics, Statistical Theory and Methods