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Random Fields for Spatial Data Modeling

This book provides an inter-disciplinary introduction to the theory of random fields and its applications. Spatial models and spatial data;

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Statistical Methods for Spatial Data Analysis

generalized linear mixed models for spatial data. It succinctly discusses Bayesian hierarchical models and concludes with reviews on simulating random;

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Statistical Methods for Spatial Data Analysis

analytical tools designed explicitly for spatial data analysis. Statistical Methods for Spatial Data Analysis answers the demand for a text that;

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Principles of Modeling Uncertainties in Spatial Data and Spatial Analyses

for spatial data and spatial analysis is an important branch of that theory. Principles of Modeling Uncertainties in Spatial Data and Spatial;

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Principles of Modeling Uncertainties in Spatial Data and Spatial Analyses

for spatial data and spatial analysis is an important branch of that theory. Principles of Modeling Uncertainties in Spatial Data and Spatial;

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Stochastic Geometry, Spatial Statistics and Random Fields: Asymptotic Methods

is focused on asymptotic methods in geometric probability including weak and strong limit theorems for random spatial structures (point processes;

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Markov Random Field Modeling in Image Analysis

; Strong Random Fields; Spatial-Temporal Models; Learning MRF for Classification. This book is an excellent reference for researchers working;

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Gaussian Markov Random Fields

Gaussian Markov Random Field (GMRF) models are most widely used in spatial statistics - a very active area of research in which few up-to;

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Gaussian Markov Random Fields

Gaussian Markov Random Field (GMRF) models are most widely used in spatial statistics - a very active area of research in which few up-to;

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Advances in Geo-Spatial Information Science

and time, spatial analysis, uncertainty modeling and geo-visualization), and new scientific and technological research initiatives for geo;

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Hierarchical Modeling and Analysis for Spatial Data

, Hierarchical Modeling and Analysis for Spatial Data, Second Edition reflects the major growth in spatial statistics as both a research area and an area;

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Spatial Microsimulation with R

Generate and Analyze Multi-Level Data Spatial microsimulation involves the generation, analysis, and modeling of individual-level data;

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Spatial Microsimulation with R

Generate and Analyze Multi-Level Data Spatial microsimulation involves the generation, analysis, and modeling of individual-level data;

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

) approach for modeling continuous spatial processes with a Matern covariance, which has been implemented using the integrated nested Laplace;

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

) approach for modeling continuous spatial processes with a Matern covariance, which has been implemented using the integrated nested Laplace;

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Analyzing and Modeling Spatial and Temporal Dynamics of Infectious Diseases

of Infectious Diseases features: * Approaches to better use infectious disease data collected from various sources for analysis and modeling purposes;

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Using R for Bayesian Spatial and Spatio-Temporal Health Modeling

in the analysis of geo-referenced spatial data are employed and code is provided. It will likely become a key reference for researchers and;

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Hybrid Random Fields

of Bayesian networks and Markov random fields, the newly introduced hybrid random fields are an interesting approach to get the best of both these;

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Scale in Spatial Information and Analysis

scales of spatial variation that exist in the measured data. It provides you with a series of tools for handling spatial data while accounting;

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Scale in Spatial Information and Analysis

scales of spatial variation that exist in the measured data. It provides you with a series of tools for handling spatial data while accounting;

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Spatial Statistics

field data-vegetation, soil, and environmental-to produce a spatial model that can be reconstructed and displayed using GIS software. Readers;

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Spatial Modeling in GIS and R for Earth and Environmental Sciences

Spatial Modeling in GIS and R for Earth and Environmental Sciences offers an integrated approach to spatial modelling using both GIS;

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Spatial Data Handling in Big Data Era

-of-the-art advances in the handling and application of spatial data, especially spatial Big Data, offering a cutting-edge reference guide for;

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Theoretical Aspects of Spatial-Temporal Modeling

explains how one may extend classical sequential Monte Carlo methods for filtering and static inference problems to high dimensions and big-data;

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Spatial Data Handling in Big Data Era

-of-the-art advances in the handling and application of spatial data, especially spatial Big Data, offering a cutting-edge reference guide for;

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Beyond Mapping

This book discusses maps as data with data structure implications; roving windows; spatial data modeling and management; assessing;

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Multiscale Analysis of Complex Time Series

and experimental data. The only modern treatment of signal processing with chaos and random fractals unified, this is an essential book for;

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