Spatial Data Analysis

Designed to be a high-level, approachable resource for engineers who need further insight into spatial temporal information systems from an ontological perspective, Spatial Temporal Information System

Mobility of people and goods is essential in the global economy. The ability to track the routes and patterns associated with this mobility offers unprecedented opportunities for developing new, smarter applications in different domains. Much of the current research is devoted to developing concepts, models, and tools to comprehend mobility data and make it manageable for these applications. This book surveys the myriad facets of mobility data, from spatio-temporal data modeling, to data aggregation and warehousing, to data analysis, with a specific focus on monitoring people in motion (drivers, airplane passengers, crowds, and even animals in the wild). Written by a renowned group of worldwide experts, it presents a consistent framework that facilitates understanding of all these different facets, from basic definitions to state-of-the-art concepts and techniques, offering both researchers and professionals a thorough understanding of the applications and opportunities made possible b

This thorough analysis of the hydrological system in one of the fastest-developing regions of Central Asia combines hydrological and demographic data to assess the future water needs of a growing popu

In this thesis the author discusses the phenomenology of supersymmetric models by means of experimental data set analysis of the electric dipole moment. There is an evaluation of the elementary proces

This book introduces the basic aspects of applied mathematics. It also covers such topics as information data manipulation, information coding, data approximation, data dimensionality reduction, data

This book combines highly accurate optical spectroscopy data on the recently discovered iron-based high-temperature superconductors with an incisive theoretical analysis.

Revision of established textbook by one of the leading international researchers and writers on panel data. Comments on the current fourth edition from leading econometricians. Includes new chapter

Looks at the techniques authorities use to prevent terrorism, including surveillance, data analysis, biodetectors, and DNA evidence.

Mixed modeling is one of the most promising and exciting areas of statistical analysis, enabling the analysis of nontraditional, clustered data that may come in the form of shapes or images. This book

"Beginning with an overview of food and food constituents, the book outlines current nutrient analysis systems, techniques for data analysis, and food labeling. The book reviews nutrition science incl

Tableau Your Data! is a comprehensive guide to the effective use of the Tableau Software toolset for data visualization. It covers the core feature set for data analytics, illustrating best practic

This collection, assembled and introduced by the esteemed editorial team of acclaimed Social Statistics, tracks the development of statistical methods for continuous or interval-scale data. The volume

A ground-up approach to explaining dynamic spatial modelling for an interdisciplinary audience.Across broad areas of the environmental and social sciences, simulation models are an important way to s

Machine learning is concerned with the analysis of large data and multiple variables. However, it is also often more sensitive than traditional statistical methods to analyze small data. The first vol

Human behavior and action is closely related to a corresponding social and spatial environment. The nature of relations in their structures, functions, and temporal domains is characterized by a duali

Bioinformatics brings computational methods to the analysis and processing of genomic data. Bioinformatics: Databases and Systems focuses on the issues of system building and data curation that domina

"High-throughput assays are part of a paradigm shift, to more cost-effective and reliable methods, in the testing of chemical and drug safety. This book covers methods, data generation, data analysis,

Recent decades have brought advances in statistical theory for missing data, which, combined with advances in computing ability, have allowed implementation of a wide array of analyses. In fact, so many methods are available that it can be difficult to ascertain when to use which method. This book focuses on the prevention and treatment of missing data in longitudinal clinical trials. Based on his extensive experience with missing data, the author offers advice on choosing analysis methods and on ways to prevent missing data through appropriate trial design and conduct. He offers a practical guide to key principles and explains analytic methods for the non-statistician using limited statistical notation and jargon. The book's goal is to present a comprehensive strategy for preventing and treating missing data, and to make available the programs used to conduct the analyses of the example dataset.

This book analyses the spatial politics of a range of British novelists writing on London since the 1950s, emphasizing spatial representation as an embodied practice at the point where the architectur

Machine learning is a novel discipline concerned with the analysis of large and multiple variables data. It involves computationally intensive methods, like factor analysis, cluster analysis, and disc

In order to help researchers and practitioners use eigenvector spatial filtering (ESF), which makes spatial statistics more accessible to very many users, Chun and Griffith (both geospatial informatio

The chapters in Human Spatial Memory: Remembering Where present a fascinating picture of an everyday aspect of mental life that is as intriguing to people outside of academia as it is to scientists st

Recent decades have brought advances in statistical theory for missing data, which, combined with advances in computing ability, have allowed implementation of a wide array of analyses. In fact, so many methods are available that it can be difficult to ascertain when to use which method. This book focuses on the prevention and treatment of missing data in longitudinal clinical trials. Based on his extensive experience with missing data, the author offers advice on choosing analysis methods and on ways to prevent missing data through appropriate trial design and conduct. He offers a practical guide to key principles and explains analytic methods for the non-statistician using limited statistical notation and jargon. The book's goal is to present a comprehensive strategy for preventing and treating missing data, and to make available the programs used to conduct the analyses of the example dataset.

Through its exploration of the spatial dimension of risk, this book offers a brand new approach to theorizing risk, and significant improvements in how to manage, tolerate and take risks. A broad rang

Taking a data-driven approach, A Course on Statistics for Finance presents statistical methods for financial investment analysis. The author introduces regression analysis, time series analysis, and m

Nearly all urban data used for the purpose of economic analysis, urban policymaking, and investment decision-making are aggregated data. Urban systems, however, are heterogeneous and complex, which re

This book analyses the long term spatial-economic metamorphosis of Schiphol and the Schiphol region as archetypal for a wider international phenomenon of urban development of metropolises across the w

The scalp and cortex lie like pages of an open book on which the cortex enciphers vast quantities of information and knowledge. They are recorded and analyzed as temporal and spatial patterns in the e

Picture It! illuminates the abilities of visual-spatial learners and describes the challenges that they have in traditional learning environments. It provides strategies that help them use their stren

Do dynamic externalities, in the form of technology creation, adoption and spatial agglomeration shape the pattern of regional growth in Europe? This study provides an alternative view on regional con

"This book is an essential collection of research on the area of data mining and analytics, presenting the most recent perspectives on data mining subjects and current issues"--Provided by publisher.

Spatial cognition is a branch of cognitive psychology that studies how people acquire and use knowledge about their environment to determine where they are, how to obtain resources, and how to find th

The analysis of variance (ANOYA) models have become one of the most widely used tools of modern statistics for analyzing multifactor data. The ANOYA models provide versatile statistical tools for stud

Survival data or more general time-to-event data occur in many areas, including medicine, biology, engineering, economics, and demography, but previously standard methods have requested that all time

Even as big data is turning the world upside down, the next phase of the revolution is already taking shape: real-time data analysis. This hands-on guide introduces you to Storm, a distributed, JVM-ba

This book focuses on the analysis of dose-response microarray data in pharmaceutical settings, the goal being to cover this important topic for early drug development experiments and to provide user-f

A major new introduction to the UK planning system. It outlines the evolution and use of the new spatial planning approach which is increasingly adopted at all levels of the UK planning system from Eu

Quantile regression analysis differs from more conventional regression models in its emphasis on distributions. Whereas standard regression procedures show how the expected value of the dependent vari

Highlighting both the theory and practice of secondary analysis and the use of secondary sources, this collection considers the nature of secondary analysis as a research tool; reflects on the definit

Computing increasingly happens somewhere, with that geographic location important to the computational process itself. Many new and evolving spatial technologies, such as geosensor networks and smartp