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Crime Mapping And Spatial Data Analysis Using R


Crime Mapping And Spatial Data Analysis Using R
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Crime Mapping And Spatial Data Analysis Using R


Crime Mapping And Spatial Data Analysis Using R
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Author : Juan Medina Ariza
language : en
Publisher: CRC Press
Release Date : 2023-04-27

Crime Mapping And Spatial Data Analysis Using R written by Juan Medina Ariza and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-04-27 with Mathematics categories.


Crime mapping and analysis sit at the intersection of geocomputation, data visualisation and cartography, spatial statistics, environmental criminology, and crime analysis. This book brings together relevant knowledge from these fields into a practical, hands-on guide, providing a useful introduction and reference material for topics in crime mapping, the geography of crime, environmental criminology, and crime analysis. It can be used by students, practitioners, and academics alike, whether to develop a university course, to support further training and development, or to hone skills in self-teaching R and crime mapping and spatial data analysis. It is not an advanced statistics textbook, but rather an applied guide and later useful reference books, intended to be read and for readers to practice the learnings from each chapter in sequence. In the first part of this volume we introduce key concepts for geographic analysis and representation and provide the reader with the foundations needed to visualise spatial crime data. We then introduce a series of tools to study spatial homogeneity and dependence. A key focus in this section is how to visualise and detect local clusters of crime and repeat victimisation. The final chapters introduce the use of basic spatial models, which account for the distribution of crime across space. In terms of spatial data analysis the focus of the book is on spatial point pattern analysis and lattice or area data analysis.



Crime Mapping And Spatial Data Analysis Using R


Crime Mapping And Spatial Data Analysis Using R
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Author : Juan Medina Ariza
language : en
Publisher: CRC Press
Release Date : 2023-04-27

Crime Mapping And Spatial Data Analysis Using R written by Juan Medina Ariza and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-04-27 with Mathematics categories.


Crime mapping and analysis sit at the intersection of geocomputation, data visualisation and cartography, spatial statistics, environmental criminology, and crime analysis. This book brings together relevant knowledge from these fields into a practical, hands-on guide, providing a useful introduction and reference material for topics in crime mapping, the geography of crime, environmental criminology, and crime analysis. It can be used by students, practitioners, and academics alike, whether to develop a university course, to support further training and development, or to hone skills in self-teaching R and crime mapping and spatial data analysis. It is not an advanced statistics textbook, but rather an applied guide and later useful reference books, intended to be read and for readers to practice the learnings from each chapter in sequence. In the first part of this volume we introduce key concepts for geographic analysis and representation and provide the reader with the foundations needed to visualise spatial crime data. We then introduce a series of tools to study spatial homogeneity and dependence. A key focus in this section is how to visualise and detect local clusters of crime and repeat victimisation. The final chapters introduce the use of basic spatial models, which account for the distribution of crime across space. In terms of spatial data analysis the focus of the book is on spatial point pattern analysis and lattice or area data analysis.



Applied Spatial Data Analysis With R


Applied Spatial Data Analysis With R
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Author : Roger S. Bivand
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-06-21

Applied Spatial Data Analysis With R written by Roger S. Bivand and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-06-21 with Medical categories.


Applied Spatial Data Analysis with R, second edition, is divided into two basic parts, the first presenting R packages, functions, classes and methods for handling spatial data. This part is of interest to users who need to access and visualise spatial data. Data import and export for many file formats for spatial data are covered in detail, as is the interface between R and the open source GRASS GIS and the handling of spatio-temporal data. The second part showcases more specialised kinds of spatial data analysis, including spatial point pattern analysis, interpolation and geostatistics, areal data analysis and disease mapping. The coverage of methods of spatial data analysis ranges from standard techniques to new developments, and the examples used are largely taken from the spatial statistics literature. All the examples can be run using R contributed packages available from the CRAN website, with code and additional data sets from the book's own website. Compared to the first edition, the second edition covers the more systematic approach towards handling spatial data in R, as well as a number of important and widely used CRAN packages that have appeared since the first edition. This book will be of interest to researchers who intend to use R to handle, visualise, and analyse spatial data. It will also be of interest to spatial data analysts who do not use R, but who are interested in practical aspects of implementing software for spatial data analysis. It is a suitable companion book for introductory spatial statistics courses and for applied methods courses in a wide range of subjects using spatial data, including human and physical geography, geographical information science and geoinformatics, the environmental sciences, ecology, public health and disease control, economics, public administration and political science. The book has a website where complete code examples, data sets, and other support material may be found: http://www.asdar-book.org. The authors have taken part in writing and maintaining software for spatial data handling and analysis with R in concert since 2003.



An Introduction To R For Spatial Analysis And Mapping


An Introduction To R For Spatial Analysis And Mapping
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Author : Chris Brunsdon
language : en
Publisher: SAGE
Release Date : 2014-04-30

An Introduction To R For Spatial Analysis And Mapping written by Chris Brunsdon and has been published by SAGE this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-04-30 with Social Science categories.


"In an age of big data, data journalism and with a wealth of quantitative information around us, it is not enough for students to be taught only 100 year old statistical methods using ′out of the box′ software. They need to have 21st-century analytical skills too. This is an excellent and student-friendly text from two of the world leaders in the teaching and development of spatial analysis. It shows clearly why the open source software R is not just an alternative to commercial GIS, it may actually be the better choice for mapping, analysis and for replicable research. Providing practical tips as well as fully working code, this is a practical ′how to′ guide ideal for undergraduates as well as those using R for the first time. It will be required reading on my own courses." - Richard Harris, Professor of Quantitative Social Science, University of Bristol R is a powerful open source computing tool that supports geographical analysis and mapping for the many geography and ‘non-geography’ students and researchers interested in spatial analysis and mapping. This book provides an introduction to the use of R for spatial statistical analysis, geocomputation and the analysis of geographical information for researchers collecting and using data with location attached, largely through increased GPS functionality. Brunsdon and Comber take readers from ‘zero to hero’ in spatial analysis and mapping through functions they have developed and compiled into R packages. This enables practical R applications in GIS, spatial analyses, spatial statistics, mapping, and web-scraping. Each chapter includes: Example data and commands for exploring it Scripts and coding to exemplify specific functionality Advice for developing greater understanding - through functions such as locator(), View(), and alternative coding to achieve the same ends Self-contained exercises for students to work through Embedded code within the descriptive text. This is a definitive ′how to′ that takes students - of any discipline - from coding to actual applications and uses of R.



Crime Mapping And Spatial Data Analysis Using R


Crime Mapping And Spatial Data Analysis Using R
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Author : Juanjo Medina
language : en
Publisher: CRC Press
Release Date : 2023

Crime Mapping And Spatial Data Analysis Using R written by Juanjo Medina and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023 with Crime analysis categories.


"Crime mapping and analysis sit at the intersection of geocomputation, data visualisation and cartography, spatial statistics, environmental criminology, and crime analysis. This book brings together relevant knowledge from these fields into a practical, hands-on guide, providing a useful introduction and reference material for topics in crime mapping, the geography of crime, environmental criminology, and crime analysis. It can be used by students, practitioners, and academics alike, whether to develop a university course, to support further training and development, or to hone skills in self-teaching R and crime mapping and spatial data analysis. It is not an advanced statistics textbook, but rather an applied guide and later useful reference books, intended to be read and for readers to practice the learnings from each chapter in sequence. In the first part of this volume we introduce key concepts for geographic analysis and representation and provide the reader with the foundations needed to visualise spatial crime data. We then introduce a series of tools to study spatial homogeneity and dependence. A key focus in this section is how to visualise and detect local clusters of crime and repeat victimisation. The final chapters introduce the use of basic spatial models, which account for the distribution of crime across space. In terms of spatial data analysis the focus of the book is on spatial point pattern analysis and lattice or area data analysis"--



Crime Mapping And Spatial Data Analysis Using R


Crime Mapping And Spatial Data Analysis Using R
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Author : Juanjo Medina
language : en
Publisher: CRC Press
Release Date : 2023

Crime Mapping And Spatial Data Analysis Using R written by Juanjo Medina and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023 with Crime analysis categories.


"Crime mapping and analysis sit at the intersection of geocomputation, data visualisation and cartography, spatial statistics, environmental criminology, and crime analysis. This book brings together relevant knowledge from these fields into a practical, hands-on guide, providing a useful introduction and reference material for topics in crime mapping, the geography of crime, environmental criminology, and crime analysis. It can be used by students, practitioners, and academics alike, whether to develop a university course, to support further training and development, or to hone skills in self-teaching R and crime mapping and spatial data analysis. It is not an advanced statistics textbook, but rather an applied guide and later useful reference books, intended to be read and for readers to practice the learnings from each chapter in sequence. In the first part of this volume we introduce key concepts for geographic analysis and representation and provide the reader with the foundations needed to visualise spatial crime data. We then introduce a series of tools to study spatial homogeneity and dependence. A key focus in this section is how to visualise and detect local clusters of crime and repeat victimisation. The final chapters introduce the use of basic spatial models, which account for the distribution of crime across space. In terms of spatial data analysis the focus of the book is on spatial point pattern analysis and lattice or area data analysis"--



Multilevel Modeling Using R


Multilevel Modeling Using R
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Author : W. Holmes Finch
language : en
Publisher: CRC Press
Release Date : 2024-04-05

Multilevel Modeling Using R written by W. Holmes Finch and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-04-05 with Reference categories.


Like its bestselling predecessor, Multilevel Modeling Using R, Third Edition provides the reader with a helpful guide to conducting multilevel data modeling using the R software environment. After reviewing standard linear models, the authors present the basics of multilevel models and explain how to fit these models using R. They then show how to employ multilevel modeling with longitudinal data and demonstrate the valuable graphical options in R. The book also describes models for categorical dependent variables in both single-level and multilevel data. The third edition of the book includes several new topics that were not present in the second edition. Specifically, a new chapter has been included, focussing on fitting multilevel latent variable modeling in the R environment. With R, it is possible to fit a variety of latent variable models in the multilevel context, including factor analysis, structural models, item response theory, and latent class models. The third edition also includes new sections in Chapter 11 describing two useful alternatives to standard multilevel models, fixed effects models and generalized estimating equations. These approaches are particularly useful with small samples and when the researcher is interested in modeling the correlation structure within higher-level units (e.g., schools). The third edition also includes a new section on mediation modeling in the multilevel context, in Chapter 11. This thoroughly updated revision gives the reader state-of-the-art tools to launch their own investigations in multilevel modeling and gain insight into their research.



Applied Survey Data Analysis


Applied Survey Data Analysis
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Author : Brady T. West
language : en
Publisher: CRC Press
Release Date : 2025-04-15

Applied Survey Data Analysis written by Brady T. West and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-04-15 with Mathematics categories.


Highly recommended by the Journal of Official Statistics, The American Statistician, and other top statistical journals, Applied Survey Data Analysis, Third Edition provides an up-to-date overview of state-of-the-art approaches to the analysis of complex sample survey data. Building on the wealth of material on practical approaches to descriptive analysis and regression modeling from the first and second editions, this third edition further expands the topics covered and presents more step-by-step examples of modern approaches to the analysis of survey data using the newest statistical software procedures. New to the Third Edition: Applied Bayesian methods for the analysis of complex sample survey data using available software implementing these methods State-of-the-art methods and software for the analysis of survey data collected from non-probability samples Software for modern applications of machine learning techniques to complex sample survey data A completely revamped website providing code for replicating all the analyses illustrated in the book using Stata, SAS, SPSS, R, Mplus, SUDAAN, WesVar, and IVEware New end-of-chapter exercises, allowing for practice implementing the methods, including Bayesian analysis exercises Updated summaries of the newest literature on the analysis of survey data collected from complex samples An updated review of software packages currently available for the analysis of complex sample survey data Designed for readers working in a wide array of disciplines who conduct secondary analyses of survey data as part of their applied work, this book continues to provide a practical and accessible guide to the analysis of survey data. Continuing to use an example-driven approach to clearly illustrate analysis methods and software, the third edition contains many new examples and practical exercises based on recent versions of real-world survey data sets. Although the authors continue to use Stata for most examples in the text, they also offer the newest code for replicating the examples in other popular software packages on the book’s revamped website.



Understanding Elections Through Statistics


Understanding Elections Through Statistics
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Author : Ole J. Forsberg
language : en
Publisher: CRC Press
Release Date : 2024-10-31

Understanding Elections Through Statistics written by Ole J. Forsberg and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-10-31 with Mathematics categories.


Elections are random events. From individuals deciding whether to vote, to individuals deciding who to vote for, to election authorities deciding what to count, the outcomes of competitive democratic elections are rarely known until election day... or beyond. Understanding Elections through Statistics explores this random phenomenon from three primary points of view: predicting the election outcome using opinion polls, testing the election outcome using government-reported data, and exploring election data to better understand the people. Written for those with only a brief introduction to statistics, this book takes you on a statistical journey from how polls are taken to how they can—and should—be used to estimate current popular opinion. Once an understanding of the election process is built, we turn toward testing elections for evidence of unfairness. While holding elections has become the de facto proof of government legitimacy, those electoral processes may hide the dirty little secret of the government, illicitly ensuring a favorable election outcome. This book includes these features designed to make your statistical journey more enjoyable: Vignettes of elections, including maps, starting each chapter to motivate the material In-chapter cues to help one avoid the heavy math—or to focus on it End-of-chapter problems designed to review and extend what was covered in the chapter Many opportunities to turn the power of the R Statistical Environment to the enclosed election data files, as well as to those you find interesting The second edition improves upon this and includes: A rewrite of several chapters to make the underlying concepts more clear A chapter dedicated to confidence intervals, what they mean, and what they do not Additional experiments to help you better understand the statistics of elections A new introduction to polling, its terms, its processes, and its ethics From these features, it is clear that the audience for this book is quite diverse. It provides the statistics and mathematics for those interested in statistics and mathematics, but it also provides detours for those who just want a good read and a deeper understanding of elections.



Foundations Of Crime Analysis


Foundations Of Crime Analysis
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Author : Jeffery T. Walker
language : en
Publisher: Routledge
Release Date : 2018-02-12

Foundations Of Crime Analysis written by Jeffery T. Walker and has been published by Routledge this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-02-12 with Social Science categories.


In recent years, the fields of crime analysis and environmental criminology have grown in prominence for their advancements made in understanding crime. This book offers a theoretical and methodological introduction to crime analysis, covering the main techniques used in the analysis of crime and the foundation of crime mapping. Coverage includes discussions of: The development of crime analysis and the profession of the crime analyst, The theoretical roots of crime analysis in environmental criminology, Pertinent statistical methods for crime analysis, Spatio-temporal applications of crime analysis, Crime mapping and the intersection of crime analysis and police work, Future directions for crime analysis. Packed with case studies and including examples of specific problems faced by crime analysts, this book offers the perfect introduction to the analysis and investigation of crime. It is essential reading for students taking courses on crime analysis, crime mapping, crime prevention, and environmental criminology. A companion website offers further resources for students, including flashcards and video and website links. For instructors, it includes chapter-by-chapter PowerPoint slides.