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Spatial Data Analysis in Ecology and Agriculture Using R

Assuming no prior knowledge of R, Spatial Data Analysis in Ecology and Agriculture Using R provides practical;

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Data Analysis in Vegetation Ecology

graduate students and postdoctoral researchers of vegetation ecology, ecological data analysis, and ecological modelling, and experienced;

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Spatial Analysis with R

: Includes new practical exercises and worked-out examples using R Presents a wide range of hands-on spatial analysis worktables and lab;

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

approximation (INLA) in the R-INLA package. Key concepts about modeling spatial processes and the SPDE approach are explained with examples using;

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

approximation (INLA) in the R-INLA package. Key concepts about modeling spatial processes and the SPDE approach are explained with examples using;

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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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Hands-On Geospatial Analysis with R and QGIS

Practical examples with real-world projects in GIS, Remote sensing, Geospatial data management and Analysis using the R programming;

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Bayesian Data Analysis in Ecology Using Linear Models with R, BUGS, and Stan

Bayesian Data Analysis in Ecology Using Linear Models with R, BUGS, and STAN examines the Bayesian and frequentist methods;

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Panel Data Econometrics with R

Panel Data Econometrics with R provides a tutorial for using R in the field of panel data econometrics. Illustrated throughout with;

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Spatial Analytics with ArcGIS

Pattern Analysis and cluster mapping made easy About This Book * Analyze patterns, clusters, and spatial relationships using ArcGIS;

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Spatial Capture-Recapture

current technology and knowledge. Spatial Capture-Recapture provides you with an extensive step-by-step analysis of many data sets using different;

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Introduction to R for Terrestrial Ecology

This textbook covers R data analysis related to environmental science, starting with basic examples and proceeding up to advanced;

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Introduction to R for Terrestrial Ecology: Basics of Numerical Analysis, Mapping, Statistical Tests and Advanced Application of R

This textbook covers R data analysis related to environmental science, starting with basic examples and proceeding up to advanced;

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Introduction to Spatial Data Analysis

guided through their first steps in the R programming language. The authors explain the fundamentals of spatial data handling and analysis;

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An Introduction to Spatial Data Analysis

guided through their first steps in the R programming language. The authors explain the fundamentals of spatial data handling and analysis;

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Modern Statistics for Modern Biology

design, and power simulations using Monte Carlo, and it even reaches networks, trees, spatial statistics, image data, and microbial ecology;

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Population Ecology in Practice

analytical approaches that are currently used in demographic, genetic, and spatial analyses in population ecology. The chapters present current;

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An Introduction to R for Spatial Analysis and Mapping

in spatial analysis and mapping.This book provides an introduction to the use of R for spatial statistical analysis, geocomputation and;

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Using R for Bayesian Spatial and Spatio-Temporal Health Modeling

professionals alike to engage in the analysis of spatial and spatio-temporal health data from a Bayesian perspective using R. The book emphasizes the;

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Applied Spatial Statistics and Econometrics

This textbook is a comprehensive introduction to applied spatial data analysis using R. Each chapter walks the reader through a different;

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Applied Spatial Statistics and Econometrics

This textbook is a comprehensive introduction to applied spatial data analysis using R. Each chapter walks the reader through a different;

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Spatial Regression Analysis Using Eigenvector Spatial Filtering

Spatial Regression Analysis Using Eigenvector Spatial Filtering provides theoretical foundations and guides practical implementation;

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Quantitative Methods in Archaeology Using R

analysis. Part III covers specialized topics in archaeology, including intra-site spatial analysis, seriation, and assemblage diversity.;

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Spatial Analysis Using Big Data

Spatial Analysis Using Big Data: Methods and Urban Applications helps readers understand the most powerful, state-of-the-art spatial;

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Analyzing Ecological Data

analysis, and spatial statistics. The second part provides 17 case studies. The case studies include topics ranging from terrestrial ecology to;

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Analyzing Ecological Data

analysis, and spatial statistics. The second part provides 17 case studies. The case studies include topics ranging from terrestrial ecology to;

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Spatial Analysis

spatial analysis of ecological data are burgeoning and many ecologists are unfamiliar with what is available and how the techniques should be used;

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