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Statistics for Spatio-Temporal Data

PROSE Award in the Mathematics category, for the book Statistics for Spatio-Temporal Data (2011), published by John Wiley and Sons. (The PROSE;

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Spatio-Temporal Statistics with R

data that are available are spatio-temporal in nature, meaning that they can be indexed by their spatial locations and time stamps. Spatio;

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Spatiotemporal Design

classical and modern treatments of network design and planning for spatial and spatio-temporal data acquisition. A common problem set is interwoven;

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Outlier Detection for Temporal Data

data streams, spatio-temporal data, network data, community distribution data, etc. Compared to general outlier detection, techniques for;

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Statistical Analysis of Spatial and Spatio-Temporal Point Patterns

material, Statistical Analysis of Spatial and Spatio-Temporal Point Patterns, Third Edition presents models and statistical methods for analyzing;

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Statistical Analysis of Spatial and Spatio-Temporal Point Patterns

material, Statistical Analysis of Spatial and Spatio-Temporal Point Patterns, Third Edition presents models and statistical methods for analyzing;

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Spatio-Temporal Methods in Environmental Epidemiology

epidemiological data. Students will learn how to identify and model patterns in spatio-temporal data as well as exploit dependencies over space and time;

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Spatial Statistics and Spatio-Temporal Data

spatio-temporal models, highlighting the Gaussian case and the binary data setting, along with the different methodologies for estimation and;

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Spatio-Temporal Methods in Environmental Epidemiology

. Students will learn how to identify and model patterns in spatio-temporal data as well as exploit dependencies over space and time to reduce bias;

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Advanced Spatial Modeling with Stochastic Partial Differential Equations Using R and INLA

models for continuous outcomes * Analysis of spatial and spatio-temporal point patterns * Coregionalization spatial and spatio;

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Advanced Spatial Modeling with Stochastic Partial Differential Equations Using R and INLA

INLA and SPDE methodologies and the R-INLA package. It also includes a wide range of applications: * Spatial and spatio-temporal models for;

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Advances in Spatio-Temporal Analysis

geographical information systems. Spatio-temporal analysis embodies spatial modelling, spatio-temporal modelling and spatial reasoning and data mining;

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Spatial & Spatio Temporal Bayesian

Spatial and Spatio-Temporal Bayesian Models with R-INLA provides a much needed, practically oriented & innovative presentation of the;

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Modern Statistical Methods for Spatial and Multivariate Data

applications such as the use of spatial and spatio-temporal models for rainfall in South Carolina and the multivariate sparse areal mixed model for the;

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Spatial Analysis

spatial analysis, for both complete census and sample data * Investigating updated treatments of spatial autocorrelation and spatio-temporal;

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Spatio-temporal Image Analysis for Longitudinal and Time-Series Image Data

This book constitutes the thoroughly refereed post-conference proceedings of the Third International Workshop on Spatio-temporal Image;

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Advances in Spatio-Temporal Segmentation of Visual Data

transform properties, as well as techniques for spatio-temporal video segmentation and interpretation, online fuzzy clustering of data streams, and;

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Spatio-temporal Analysis and Optimization of Land Use/Cover Change

optimization study fields. Firstly, three spatio-temporal logit models for land use change analysis, namely, geographically and temporally weighted;

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Spatio-temporal Analysis and Optimization of Land Use/Cover Change

optimization study fields. Firstly, three spatio-temporal logit models for land use change analysis, namely, geographically and temporally weighted;

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Computing in Geographic Information Systems

is emerging as a platform for scientific visualization, simulation, and computation of spatio-temporal data. New computing techniques are being;

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Computing in Geographic Information Systems

is emerging as a platform for scientific visualization, simulation, and computation of spatio-temporal data. New computing techniques are being;

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Using R for Bayesian Spatial and Spatio-Temporal Health Modeling

in such studies of disease. Using R for Bayesian Spatial and Spatio-Temporal Health Modeling provides a major resource for those interested;

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Spatio-Temporal Databases

spatio-temporal databases of moving objects. The brief begins with the definition of flexible pattern queries, which are powerful because of the;

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Object-Oriented Design for Temporal GIS

they can be used for modelling spatio-temporal data, and how these components are developed and maintained within a GIS. It also offers;

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Object-Oriented Design for Temporal GIS

they can be used for modelling spatio-temporal data, and how these components are developed and maintained within a GIS. It also offers;

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Statistical Methods for Spatio-Temporal Systems

Statistical Methods for Spatio-Temporal Systems presents current statistical research issues on spatio-temporal data modeling and will;

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Crowdsourcing of Sensor Cloud Services

frameworks focuses on spatio-temporal composition of crowdsourced sensor-cloud services, which is a new territory for existing service oriented;

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