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Statistics for Spatio-Temporal Data book

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

Statistics for Spatio-Temporal Data



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


The following is a partial look at an interesting but slightly pointy headed study published in Nature Magazine about how much identity information can be gleaned about the identity of a subject with merely four human data points. My main focus of research is in mathematical statistics and applied probability, particularly in relation to spatial data sets and computational problems as covered in the research areas known as spatial statistics, stochastic geometry, simulation- based inference, Markov chain Monte Carlo methods, and perfect simulation. We extend the spatio-temporal data mining framework that we have developed earlier to analyze and manage such data [5]. Radius of gyration, root mean square deviation (RMSD)) to identify similar 3D conformations in folding trajectories. It is, however, far more complex than traditional databases, since the management and analysis of spatial data must be considered in three-dimensions and spatial analysis goes beyond the scope of standard statistics. Job Duties (i) Develop and validate multivariate statistical models of spatiotemporal renewable energy fields, based on data sets of disparate spatiotemporal resolution and extent. High-Dimensional Statistical Inference; Spatio-Temporal Data Applications; Computational Algorithms for High-Dimensional Data; Genomic Applications. In fact, in a dataset where the location of an individual is specified hourly, and with a spatial resolution equal to that given by the carrier's antennas, four spatio-temporal points are enough to uniquely identify 95% of the individuals. This framework is designed to analyze spatio-temporal data produced in several scientific domains. Thesis Most of my recent books and papers deal with statistical inference and computational methods for spatial and spatio-temporal point processes. Previously, researchers have examined several summary statistics (e.g.

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