Science-Based Spatiotemporal Statistics

Practical Guide with Environmental and Human Exposure Applications
1. Auflage 2028
ISBN: 978-1-4822-3803-7
Verlag: Taylor & Francis Inc

Buch, Englisch, 350 Seiten, Format (B × H): 156 mm x 234 mm

Reihe: Chapman & Hall/CRC Applied Environmental Statistics

This book provides an introduction to the theoretical development and practical methodology of the so-called science-based spatiotemporal statistics. The book capitalizes on the significance of integrating different knowledge sources (physical, ecological, health, and social) into formal spatiotemporal statistics and provides an array of practical procedures for incorporating these sources into composite space-time analysis, modeling, and estimation/prediction.

Zielgruppe

This book is intended for investigators and practitioners in the fields of statistics, geostatistics, applied sciences and engineering. It also would be useful to undergraduate- and graduate-level students in the fields of statistics, biostatistics, environment, ecology, public health, epidemiology, geography and earth and atmospheric sciences.

Autoren/Hrsg.

Christakos, George

Yu, Hwa-Lung

Inhaltsverzeichnis

Introduction. A review of spatiotemporal statistics. Science-based vs. data-processing statistics. Space-time metrics: Euclidean (spatially isotropic and non-isotropic). Non-Euclidean (river network, gravity model, isomap). Spatiotemporal random field theory (S/TRF): Ordinary S/TRF. Generalized S/TRF. Spatiotemporal statistics of data sets. Standard two-point statistics: Ordinary covariance and variogram. Generalized covariance and variogram. Extension to multi-point statistics. Spatiotemporal exploratory analysis (pattern recognition). Empirical orthogonal method: Atmospheric and hydrological applications. Dynamic factor analysis: Ecological and environmental applications. Spatiotemporal clustering analysis: SaTscan and other works. Spatiotemporal statistics of differential equations. The analytical approach: Closed form expressions of physical and biophysical laws. Low- and high-order (diagrammatic) approximations of groundwater flow. The numerical approach: First order second moment (FOSM) method. Adjoint method. Spatiotemporal trend analysis. Non-parametric approaches. The generalized additive model. The Kernel smoothing method. Spatiotemporal regression.

Über Autor(innen)

George Christakos is a distinguished professor and S.M. Birch Endowed Chair of the Department of Geography at San Diego State University, California, USA. He is also a Yongqian Chair Professor of the College of Environmental and Resource Sciences at Zhejiang University, China.

Hwa-Lung Yu is an associate professor of the Department of Bioenvironmental Systems Engineering at National Taiwan University, Taipei.