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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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Data Analysis and Statistics for Geography, Environmental Science, and Engineering

into multiple regression, dependent random processes and autoregressive time series, spatial analysis using geostatistics and spatial;

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Spatial Analysis Methods and Practice

analysis; analyzing geographic distributions and point patterns; spatial autocorrelation; spatial clustering; geographically weighted regression;

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Spatial Analysis Methods and Practice

analysis; analyzing geographic distributions and point patterns; spatial autocorrelation; spatial clustering; geographically weighted regression;

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Spatial Filtering Velocimetry

analysis, spatial filtering devices and systems, plus applications. Also suitable as a tutorial for students and users who are unfamiliar 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 Regression Models

concepts using well known international, comparative, and national examples of spatial regression analysis. Each example is presented alongside;

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Data Analysis and Statistics for Geography, Environmental Science, and Engineering

multiple regression, dependent random processes and autoregressive time series, spatial analysis using geostatistics and spatial regression;

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Three Essays on Site Specific Management

Using multivariate analysis, spatial regression, and dynamic programming, this collection of essays investigates the adoption and economic;

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

physical barriers * Survival analysis with spatial effects * Dynamic space-time regression * Spatial and spatio-temporal;

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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 Regression Models

Demonstrating the use of spatial analysis in the social sciences within a regression framework, the second edition of this text employs;

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Statistical Methods for Spatial Data Analysis

Understanding spatial statistics requires tools from applied and mathematical statistics, linear model theory, regression, time series, and;

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Statistical Methods for Spatial Data Analysis

thorough analysis of spatial regression, providing a detailed development of linear models with uncorrelated errors, linear models with spatially;

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Introduction to Spatial Econometrics

Although interest in spatial regression models has surged in recent years, a comprehensive, up-to-date text on these approaches does not;

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Introduction to Spatial Econometrics

Although interest in spatial regression models has surged in recent years, a comprehensive, up-to-date text on these approaches does not;

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Spatial Statistics

statistics, and inverse distance weighting Geospatial statistics analysis using stepwise regression, ordinary least squares (OLS;

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Spatial Analysis in Geomorphology

Originally published in 1972. This book covers from 'linear' statistical methods, regression and variance analysis to multivariate methods;

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Spatial Analysis in Geomorphology

Originally published in 1972. This book covers from 'linear' statistical methods, regression and variance analysis to multivariate methods;

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Spatial Regression Models for the Social Sciences

Focusing on the methods that are commonly used by social scientists, this text introduces the regression methods for analysing spatial data.;

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Statistical Methods for Spatial Planning and Monitoring

The book aims to investigate methods and techniques for spatial statistical analysis suitable to model spatial information in support;

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Spatial Statistics

Geospatial statistics analysis using stepwise regression, ordinary least squares (OLS), variogram, kriging, spatial auto-regression, binary;

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Understanding Crime

Spatial regression analysis, including geographically weighted regression Determining crime risk, and where crime is likely to happen Performing;

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Modern Policing Using ArcGIS Pro

Policing Using ArcGIS Pro is an easy-to-use hands-on guide for crime analysts of any skill level. Crime mapping and spatial analysis play a key;

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Geographically Weighted Regression

Geographical Weighted Regression (GWR) is a new local modelling technique for analysing spatial analysis. This technique allows local as;

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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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Geostatistical Functional Data Analysis

new reference Geostatistical Functional Data Analysis presents a unified approach to modelling functional data when spatial and spatio;

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