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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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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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Statistics for Spatio-Temporal Data

demand for statistical analyses of data that take spatial, temporal, and spatio-temporal information into account. Statistics for Spatio-Temporal;

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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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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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Spatial Analysis

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

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

Modeling spatial and spatio-temporal continuous processes is an important and challenging problem in spatial statistics. Advanced Spatial;

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

Modeling spatial and spatio-temporal continuous processes is an important and challenging problem in spatial statistics. Advanced Spatial;

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Spatio-Temporal Methods in Environmental Epidemiology

. It describes traditional and Bayesian approaches and presents the theory of spatial, temporal, and spatio-temporal modeling in the context;

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Spatio-Temporal Methods in Environmental Epidemiology

describes traditional and Bayesian approaches and presents the theory of spatial, temporal, and spatio-temporal modeling in the context of its;

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Enhanced Bayesian Network Models for Spatial Time Series Prediction: Recent Research Trend in Data-Driven Predictive Analytics

models, especially Bayesian networks (BNs), for applied research on spatialspatio-temporal data. Students of any other discipline of engineering;

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Enhanced Bayesian Network Models for Spatial Time Series Prediction

models, especially Bayesian networks (BNs), for applied research on spatialspatio-temporal data. Students of any other discipline of engineering;

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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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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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Spatial Statistics and Spatio-Temporal Data

In the spatial or spatio-temporal context, specifying the correct covariance function is fundamental to obtain efficient predictions, and;

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Semantic Kriging for Spatio-temporal Prediction

parameters. The spatial and spatio-temporal prediction of these parameters are important for the scientific community, and the semantic kriging (SemK;

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Semantic Kriging for Spatio temporal Prediction

parameters. The spatial and spatio-temporal prediction of these parameters are important for the scientific community, and the semantic kriging (SemK;

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Spatial Cluster Modelling

sampling of cluster processes, partitioning in space and space-time, spatial and spatio-temporal process modelling, nonparametric methods for;

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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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Advances in Spatial and Temporal Databases

This book constitutes the refereed proceedings of the 14th International Symposium on Spatial and Temporal Databases, SSTD 2015, held;

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Geospatial Health Data

Shiny describes spatial and spatio-temporal statistical methods and visualization techniques to analyze georeferenced health data in R. The book;

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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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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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Spatiotemporal Analysis of Extreme Hydrological Events

Spatio-temporal Analysis of Extreme Hydrological Events offers an extensive view of the experiences and applications of the latest;

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