Spatial Data Analysis

Data Preprocessing for Data Mining addresses one of the most important issues within the well-known Knowledge Discovery from Data process. Data directly taken from the source will likely have inconsis

This book first introduces the criterion of REstricted Maximum Likelihood (REML) for the fitting of a mixed model to data before illustrating how to apply mixed model analysis to a wide range of situa

The problem of privacy-preserving data analysis has a long history spanning multiple disciplines. As electronic data about individuals becomes increasingly detailed, and as technology enables ever mor

Based on an analysis of more than 150 permanent memorials to the casualties of the Troubles on public soil in the city of Belfast, Viggiani interrogates the spatial and temporal occurrence of forms of

The book focuses on molecular evolution and phylogenetics, dealing with the statistical methods of data analysis implemented in commonly-used computer software.

This major study of animal orientation in space launches the Princeton Series in Neurobiology and Behavior. Bringing together for the first time the important work done on spatial orientation over the

In Time Series Analysis and Adjustment the authors explain how the last four decades have brought dramatic changes in the way researchers analyze economic and financial data on behalf of economic and

This entry-level text offers clear and concise guidelines on how to select, construct, interpret, and evaluate count data. Written for researchers with little or no background in advanced statistics, the book presents treatments of all major models using numerous tables, insets, and detailed modeling suggestions. It begins by demonstrating the fundamentals of modeling count data, including a thorough presentation of the Poisson model. It then works up to an analysis of the problem of overdispersion and of the negative binomial model, and finally to the many variations that can be made to the base count models. Examples in Stata, R, and SAS code enable readers to adapt models for their own purposes, making the text an ideal resource for researchers working in health, ecology, econometrics, transportation, and other fields.

This entry-level text offers clear and concise guidelines on how to select, construct, interpret, and evaluate count data. Written for researchers with little or no background in advanced statistics, the book presents treatments of all major models using numerous tables, insets, and detailed modeling suggestions. It begins by demonstrating the fundamentals of modeling count data, including a thorough presentation of the Poisson model. It then works up to an analysis of the problem of overdispersion and of the negative binomial model, and finally to the many variations that can be made to the base count models. Examples in Stata, R, and SAS code enable readers to adapt models for their own purposes, making the text an ideal resource for researchers working in health, ecology, econometrics, transportation, and other fields.

Table of Contents: 1. Data and Distributions 2. Numerical Summary Measures 3. Bivariate and Multivariate Data 4. Obtaining Data 5. Probability and Sampling Distributions 6. Quality and Reliability 7. Estimation and Statistical Intervals 8. Testing Statistical Hypotheses 9. The Analysis of Variance 10. Experimental Design 11. Inferential Methods in Regression and Correlation

This book investigates several classes of partial differential equations of real time variable and complex spatial variables, including the heat, Laplace, wave, telegraph, Burgers, Black–Merton–Schole

This book provides an accessible approach to Bayesian computing and data analysis, with an emphasis on the interpretation of real data sets.

The growth of social media over the last decade has revolutionized the way individuals interact and industries conduct business. Individuals produce data at an unprecedented rate by interacting, sharing, and consuming content through social media. Understanding and processing this new type of data to glean actionable patterns presents challenges and opportunities for interdisciplinary research, novel algorithms and tool development. Social Media Mining integrates social media, social network analysis, and data mining to provide a coherent platform to understand the basics and potentials of social media mining. It introduces the unique problems arising from social media data and presents fundamental concepts, emerging issues, and effective algorithms for network analysis and data mining. Suitable for use in advanced undergraduate and beginning graduate courses as well as professional short courses, the text contains exercises of different degrees of difficulty that improve understanding

Code and Methods for Creating High-Quality Data GraphicsA data graphic is not only a static image, but it also tells a story about the data. It activates cognitive processes that are able to detect pa

Spatial Ecologies takes a new look at the spatial turn in French cultural and critical theory since 1968. Verena Andermatt Conley examines how Henri Lefebvre, Michel de Certeau, Jean Baudrillard, Marc

Written for animal researchers, this book provides a comprehensive guide to the design and statistical analysis of animal experiments. It has long been recognised that the proper implementation of these techniques helps reduce the number of animals needed. By using real-life examples to make them more accessible, this book explains the statistical tools employed by practitioners. A wide range of design types are considered, including block, factorial, nested, cross-over, dose-escalation and repeated measures and techniques are introduced to analyse the experimental data generated. Each analysis technique is described in non-mathematical terms, helping readers without a statistical background to understand key techniques such as t-tests, ANOVA, repeated measures, analysis of covariance, multiple comparison tests, non-parametric and survival analysis. This is also the first text to describe technical aspects of InVivoStat, a powerful open-source software package developed by the authors

Written for animal researchers, this book provides a comprehensive guide to the design and statistical analysis of animal experiments. It has long been recognised that the proper implementation of these techniques helps reduce the number of animals needed. By using real-life examples to make them more accessible, this book explains the statistical tools employed by practitioners. A wide range of design types are considered, including block, factorial, nested, cross-over, dose-escalation and repeated measures and techniques are introduced to analyse the experimental data generated. Each analysis technique is described in non-mathematical terms, helping readers without a statistical background to understand key techniques such as t-tests, ANOVA, repeated measures, analysis of covariance, multiple comparison tests, non-parametric and survival analysis. This is also the first text to describe technical aspects of InVivoStat, a powerful open-source software package developed by the authors

Edited by Dr Rob Kitchen, Director of the National Institute of Regional and Spatial Analysis (NIRSA) at the National University of Ireland, the Key Concepts in Human Geography series is an innovative

Edited by Dr Rob Kitchen, Director of the National Institute of Regional and Spatial Analysis (NIRSA) at the National University of Ireland, the Key Concepts in Human Geography series is an innovative

This is a state-of-the-art interpretive presentation of satellite image data, and analysis of the current state of the world's glaciers. Experts in satellite image analysis of glaciers analyze and int

The application of Geographic Information Systems (GIS) to issues in history is among the most exciting developments in both digital and spatial humanities. Describing a wide variety of applications,

The application of Geographic Information Systems (GIS) to issues in history is among the most exciting developments in both digital and spatial humanities. Describing a wide variety of applications,

Risk has always been central to finance, and managing risk depends critically on information. As evidenced by recent events, the need has never been greater for skills, systems and methodologies to manage risk information in financial markets. Authored by leading figures in risk management and analysis, this handbook serves as a unique and comprehensive reference for the technical, operational, regulatory and political issues in collecting, measuring and managing financial data. It is targeted towards a wide range of audiences, from financial industry practitioners and regulators responsible for implementing risk management systems, to system integrators and software firms helping to improve such systems. Volume 2 describes a structural and operational framework for managing a financial risk data repository. As experience accumulates on managing modern risk systems, the knowledge base of practical lessons grows. Understanding these issues and leading practices may mean the difference b

This book investigates novel methods and technologies for the collection, analysis, and representation of real-time user-generated data at the urban scale in order to explore potential scenarios for m

Continual improvements in data collection and processing have had a huge impact on brain research, producing data sets that are often large and complicated. By emphasizing a few fundamental principles

The amount of data in medical databases doubles every 20 months, and physicians are at a loss to analyze them. Also, traditional methods of data analysis have difficulty to identify outliers and patte

Ideal for students and practitioners working in spatial planning, the Europeanization of planning agendas and regional policy in general Spatial Planning Systems and Practices in Europe develops a sys

Ideal for students and practitioners working in spatial planning, the Europeanization of planning agendas and regional policy in general Spatial Planning Systems and Practices in Europe develops a sys

This book presents recent methods for Systems Genetics (SG) data analysis, applying them to a suite of simulated SG benchmark datasets. Each of the chapter authors received the same datasets to evalua

This collection brings together international scholars pursuing cutting-edge research on spatial identities under National Socialism. They demonstrate that the spatial identities of the Third Reich ca

Circular Statistics in R provides the most comprehensive guide to the analysis of circular data in over a decade. Circular data arise in many scientific contexts whether it be angular directions such

'Big data' poses challenges that require both classical multivariate methods and contemporary techniques from machine learning and engineering. This modern text equips you for the new world - integrating the old and the new, fusing theory and practice and bridging the gap to statistical learning. The theoretical framework includes formal statements that set out clearly the guaranteed 'safe operating zone' for the methods and allow you to assess whether data is in the zone, or near enough. Extensive examples showcase the strengths and limitations of different methods with small classical data, data from medicine, biology, marketing and finance, high-dimensional data from bioinformatics, functional data from proteomics, and simulated data. High-dimension low-sample-size data gets special attention. Several data sets are revisited repeatedly to allow comparison of methods. Generous use of colour, algorithms, Matlab code, and problem sets complete the package. Suitable for master's/graduat

Intelligent multimedia surveillance concerns the analysis of multiple sensing inputs including video and audio streams, radio-frequency identification (RFID), and depth data. These data are processed

The Seismic Analysis Code (SAC) is one of the most widely used analysis packages for regional and teleseismic seismic data. For the first time, this book provides users at introductory and advanced levels with a complete guide to SAC. It leads new users of SAC through the steps of learning basic commands, describes the SAC processing philosophy, and presents its macro language in full, supported throughout with example inputs and outputs from SAC. For more experienced practitioners, the book describes SAC's many hidden features, including advanced graphics aspects, its file structure, how to write independent programs to access and create files, and much more. Tutorial exercises engage users with newly acquired skills, providing data and code to implement the standard methods of teleseismic shear-wave splitting and receiver function analysis. Methodical and authoritative, this is a key resource for researchers and graduate students in global seismology, earthquake seismology and geophy

The Seismic Analysis Code (SAC) is one of the most widely used analysis packages for regional and teleseismic seismic data. For the first time, this book provides users at introductory and advanced levels with a complete guide to SAC. It leads new users of SAC through the steps of learning basic commands, describes the SAC processing philosophy, and presents its macro language in full, supported throughout with example inputs and outputs from SAC. For more experienced practitioners, the book describes SAC's many hidden features, including advanced graphics aspects, its file structure, how to write independent programs to access and create files, and much more. Tutorial exercises engage users with newly acquired skills, providing data and code to implement the standard methods of teleseismic shear-wave splitting and receiver function analysis. Methodical and authoritative, this is a key resource for researchers and graduate students in global seismology, earthquake seismology and geophy

The purpose of this book is to introduce, discuss, illustrate, and evaluate the colorful palette of analytical techniques that can be applied to the analysis of household survey data, with an emphasis

Modern analysis of HEP data needs advanced statistical tools to separate signal from background. This is the first book which focuses on machine learning techniques. It will be of interest to almost e

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