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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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Bayesian Disease Mapping

Since the publication of the second edition, many new Bayesian tools and methods have been developed for space-time data analysis, the;

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Bayesian Disease Mapping

Since the publication of the second edition, many new Bayesian tools and methods have been developed for space-time data analysis, the;

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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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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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Statistical Methods for Spatial Data Analysis

as well as practical methods for the analysis of spatial data. This book is a comprehensive and illustrative treatment of basic statistical;

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Statistical Methods for Spatial Data Analysis

as well as practical methods for the analysis of spatial data. This book is a comprehensive and illustrative treatment of basic;

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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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Bayesian Disease Mapping

in Spatial Epidemiology provides an overview of the main areas of Bayesian hierarchical modeling and its application to the geographical analysis;

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Hierarchical Modeling and Inference in Ecology

A guide to data collection, modeling and inference strategies for biological survey data using Bayesian and classical statistical methods;

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Applied Hierarchical Modeling in Ecology: Analysis of Distribution, Abundance and Species Richness in R and BUGS

Applied Hierarchical Modeling in Ecology: Analysis of Distribution, Abundance and Species Richness in R and BUGS, Volume Two: Dynamic and;

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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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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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Bayesian Methods For Data Analysis

Broadening its scope to nonstatisticians, Bayesian Methods for Data Analysis, Third Edition provides an accessible introduction to the;

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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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Applied Hierarchical Modeling in Ecology: Analysis of distribution, abundance and species richness in R and BUGS

of hierarchical models for plant and animal distribution, abundance, and community characteristics such as species richness using data collected;

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Spatial Data Analysis

Spatial Data Analysis: Theory and Practice, first published in 2003, provides a broad ranging treatment of the field of spatial data;

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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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Hybrid Systems Biology

information including learning for biological systems, parametric synthesis and inference; stochastic and hybrid models in biology; hierarchical;

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Introduction to Hierarchical Bayesian Modeling for Ecological Data

Modeling for Ecological Data gives readers a flexible and effective framework to learn about complex ecological processes from various sources;

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Introduction to Hierarchical Bayesian Modeling for Ecological Data

Modeling for Ecological Data gives readers a flexible and effective framework to learn about complex ecological processes from various sources;

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Spatial Data Handling in Big Data Era

discovery, space-time modeling, and geological applications. Spatial analysis and data mining are increasingly facing the challenges of Big Data;

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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

analysis with spatial effects * Dynamic space-time regression * Spatial and spatio-temporal models for extremes * Hurdle models with;

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Spatial Analysis

spatial data analysis, spatial autocorrelation, spatial interpolation, spatial regression, and simulation and modeling, among many others. The;

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Spatial Data Handling in Big Data Era

discovery, space-time modeling, and geological applications. Spatial analysis and data mining are increasingly facing the challenges of Big Data;

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