Spatial Data Analysis

Uneven Urbanscape takes a new theoretically grounded view of how society produces and reproduces ethnoracial economic inequality. Drawing on empirically rich documentation and quantitative analysis utilizing multiple data sources, including the US Bureau of the Census, Ong and Gonzalez assess the patterns, causes, and consequences of urban spatial disparities, specifically in home ownership, employment, and education. They focus on the global city of Los Angeles in order to examine outcomes across small geographic units that approximate neighborhoods and places, and to analyze the location-specific effects of geographic access and isolation within the region. Using a mix of micro-level data and aggregated statistics, Uneven Urbanscape provides one of the most comprehensive understandings of urban ethnoracial disparities and inequalities from 1960 to the present day.

Uneven Urbanscape takes a new theoretically grounded view of how society produces and reproduces ethnoracial economic inequality. Drawing on empirically rich documentation and quantitative analysis utilizing multiple data sources, including the US Bureau of the Census, Ong and Gonzalez assess the patterns, causes, and consequences of urban spatial disparities, specifically in home ownership, employment, and education. They focus on the global city of Los Angeles in order to examine outcomes across small geographic units that approximate neighborhoods and places, and to analyze the location-specific effects of geographic access and isolation within the region. Using a mix of micro-level data and aggregated statistics, Uneven Urbanscape provides one of the most comprehensive understandings of urban ethnoracial disparities and inequalities from 1960 to the present day.

The methods and techniques presented in this book are focused on spatial data and its use in monitoring agricultural resources, farm management, and regional markets. Spatial econometrics models are i

This text closely examines ideas, analysis, and implementation details of data structures as a specialised topic in applied algorithms. It looks at efficient ways to realise query and update operations on sets of numbers, intervals, or strings by various data structures, including: search trees; structures for sets of intervals or piece-wise constant functions; orthogonal range search structures; heaps; union-find structures; dynamization and persistence of structures; structures for strings; and hash tables. Instead of relegating data structures to trivial material used to illustrate object-oriented programming methodology, this is the first volume to show data structures as a crucial algorithmic topic. Numerous code examples in C and more than 500 references make Advanced Data Structures an indispensable text.

Covering a key topic due to growing research into the role of signaling mechanisms in toxicology, this book focuses on practical approaches for informatics, big data, and complex data sets. Combines

Carry out a variety of advanced statistical analyses including generalized additive models, mixed effects models, multiple imputation, machine learning, and missing data techniques using R. Each chapt

How is qualitative data actually collected, analyzed, and accomplished? How Qualitative Data Analysis Happens: Moving Beyond "Themes Emerged" offers an in-depth look into how qualitative social scienc

How is qualitative data actually collected, analyzed, and accomplished? How Qualitative Data Analysis Happens: Moving Beyond "Themes Emerged" offers an in-depth look into how qualitative social scienc

Written in lucid language, this valuable textbook brings together fundamental concepts of data mining and data warehousing in a single volume. Important topics including information theory, decision tree, Naïve Bayes classifier, distance metrics, partitioning clustering, associate mining, data marts and operational data store are discussed comprehensively. The textbook is written to cater to the needs of undergraduate students of computer science, engineering and information technology for a course on data mining and data warehousing. The text simplifies the understanding of the concepts through exercises and practical examples. Chapters such as classification, associate mining and cluster analysis are discussed in detail with their practical implementation using Weka and R language data mining tools. Advanced topics including big data analytics, relational data models and NoSQL are discussed in detail. Pedagogical features including unsolved problems and multiple-choice questions are

Providing information from data preparation and mean, median and mode, to regression, Lisa Daniels and Nicholas Minot use concise descriptions to help students understand the concepts behind statistic

This book uses literary analysis and digital humanities to show how social justice can be enacted in everyday actions through changing the way we think about lived spaces. As corporate and state power

This introductory textbook explains the concepts and methods of data and error analysis needed for laboratory experiment write-ups, especially physics and engineering experiments. The book contains th

This book addresses and examines the impacts of applications and services for data management and analysis, such as infrastructure, platforms, software, and business processes, on both academia and in

This unique guide brings together all the skills you need to get started with data science -- one of the world’s fastest growing fields! Leading data science instructors Michael Freeman and Joel

The edited collection provides an analysis of the effects of the global spread of contemporary capitalism that includes predatory practices such as harmful loan conditions, highly speculative investme

This book presents conjectural advances in big data analysis, machine learning and computational intelligence, as well as their potential applications in scientific computing. It discusses major issue

High spatial remote sensing data have been often used as valuable sources of information throughout emergency management cycle. Information extracted in high spatial remote sensing data right after a

Statistical analysis is common in the social sciences, and among the more popular programs is R. This book provides a foundation for undergraduate and graduate students in the social sciences on how t

Statistical analysis is common in the social sciences, and among the more popular programs is R. This book provides a foundation for undergraduate and graduate students in the social sciences on how t

This book thoroughly covers the remote sensing visualization and analysis techniques based on computational imaging and vision in Earth science. Remote sensing is considered a significant informa

Since the publication of the second edition, many new Bayesian tools and methods have been developed for space-time data analysis, the predictive modeling of health outcomes, and other spatial biostat

This book offers new transparent views and step-by-step methods for performance evaluation of a set of units using Data Envelopment Analysis (DEA). The book has twelve practical chapters. Elementary c

This proceedings volume presents new methods and applications in applied economic research with an emphasis on advances in panel data analysis. Featuring papers presented at the 2017 International Con

An Insightful Examination of Smart Water Systems and Technology Inland water supplies are under increasing pressure. Climate, social, and demographic change have begun tipping the balance toward deman

"This book explores the extraction and prediction of patterns at multiple levels of abstraction. It involves a procedure handling both numeric and nominal data at once using a single method and the me

Genomics researchers today are faced with an ever-increasing amount of data to analyze, and yet they have a difficult time leveraging modern frameworks and technologies (like Spark and cloud infrastru

This book assembles and organizes a selected range of methods and techniques that every planning practitioner should know to be successful in the contemporary global urban landscape. The book is uniqu

The creation, accumulation, and use of copious amounts of data are driving rapid change across a wide variety of industries and academic disciplines. This ‘Big Data’ phenomenon is the result of recent

Deconstructing 10 Actual, Official LSAT PrepTests Volume VI Taking a practice test is great prep for the LSAT, but reviewing a practice test afterward is where you really improve. Supercharge your LS

The programming landscape of natural language processing has changed dramatically in the past few years. Machine learning approaches now require mature tools like Python’s scikit-learn to apply

This book highlights recent advances in intelligent data analysis, computational intelligence, signal processing, and all associated applications of artificial intelligence.

The second of a two volume set on novel methods in harmonic analysis, this book draws on a number of original research and survey papers from well-known specialists detailing the latest innovations an

This book addresses the impacts of various types of services such as infrastructure, platforms, software, and business processes that cloud computing and Big Data have introduced into business. Featur

This book presents contributions on topics ranging from novel applications of topological analysis for particular problems, through studies of the effectiveness of modern topological methods, algorith

This is a solution-oriented book providing an end-to-end look at building Internet-of-Things solutions using the Microsoft Azure IoT Suite. You'll learn about data acquisition and analysis, even real-

Master functions and discover how to write functional programs in R. In this concise book, you'll make your functions pure by avoiding side-effects; you’ll write functions that manipulate other functi

This book offers an easily accessible treatment of the theory and practice of digital data communications, explaining how to design, implement, and test software-defined radio modems. System analysts