Statistics for Spatio-Temporal Data by Noel Cressie, Christopher K. Wikle

Statistics for Spatio-Temporal Data Noel Cressie, Christopher K. Wikle ebook
Publisher: Wiley
Page: 624
ISBN: 0471692743, 9780471692744
Format: epub

Department name when degree awarded. Hierarchical spatial, temporal, and spatio-temporal models allow for the simultaneous modeling of both first and second order processes, thus accounting for underlying autocorrelation in the system while still providing insight into overall Based on preliminary analysis, the data appeared to be overdispersed, containing a disproportionately high number of zeros along with a high variance relative to the mean. The postdoctoral fellow will develop and implement cutting-edge statistical methodologies with the goal of improving the analysis of high-dimensional spatio-temporal survey data. In this case, he and de Montjoye were able to use those tools to uncover a simple mathematical relationship between the resolution of spatiotemporal data and the likelihood of identifying a member of a data set. Hidalgo's group specializes in applying the tools of statistical physics to a wide range of subjects, from communications networks to genetics to economics. This pipeline has been successfully applied to obtain quantitative gene expression data at cellular resolution in space and at 6.5-min resolution in time. Each virus was assigned a unique identification number, allowing us to link geographic location, genetic sequence and temporal data in later analyses, and the dataset was sorted in ascending order by this unique ID. If there is spatial autocorrelation in model residuals, values are typically low and the semivariance increases with separation distance [30,31]. The seNorge model provides a relatively simple, not very data-demanding, yet still process-based method to construct snow maps of high spatiotemporal resolution. Based on this hypothesis, we combined spatial statistical methods with genetic analytic techniques and explicitly used geographic space to explore genetic evolution of H5N1 highly pathogenic avian influenza viruses at the sub-national scale in Vietnam. Are there better metaphors for spatio-temporal data visualization than a time-evolving heat map? Statistics for Spatio-Temporal Data (Wiley Desktop Editions) book download Download Statistics for Spatio-Temporal Data (Wiley Desktop Editions) Wiley-VCH - Cressie, Noel / Wikle, Christopher K. The vision of a data-intensive science hopes that the open availability of data with a higher spatial, temporal, and thematic resolution will enable us to better address complex scientific and social questions. The main task will be the development and evaluation of dynamic visualisation methods for spatio-temporal data by combining techniques of computer graphics and statistical analysis. Boundaries of spatial units may evolve across time and that adds another layer of mismatches to a spatio-temporal level. Dimensional geo-referenced visualization but spatio-temporal data requires at least four dimensions for visualization. €I use the spatial statistics technique known as co-kriging to fuse multi-sensor land surface temperature images.” Yang uses an algorithm he devised to fill the spatiotemporal gaps between the two data sets. In this paper the set of equations contained in the seNorge model code is described and a~thorough spatiotemporal statistical evaluation of the model performance in 1957–2011 is made using the two major sets of extensive in-situ snow measurements that exist for Norway.