Spatial Data Analysis

In order to gain an understanding of the dynamics of human individual and average growth patterns it is essential that the right methods are selected. There are a variety of methods available to analyse individual growth patterns, to estimate variation in different growth measures in populations and to relate genetic and environmental factors to individual and average growth. This volume provides an overview of modern techniques for the assessment and collection of growth data and methods of analysis for individual and population growth data. The book contains the basic mathematical and statistical tools required to understand the concepts of the methods under discussion and worked examples of analyses, but it is neither a mathematical treatise, nor a recipe book for growth data analysis. Aimed at junior and senior researchers involved in the analysis of human growth data, this book will be an essential reference for anthropologists, auxologists and paediatricians.

Previc, a human factors specialist who formerly led the Air Force's Spatial Disorientation Countermeasures Task Group, and Ercoline (disorientation countermeasures, the Air Force's School of Aerospace

This book illustrates a set of tools - story grammars, relational data models, and network models - that can be profitably used for the collection, organization, and analysis of narrative data in socio-historical research. A story grammar, or Subject-Action-Object and their modifiers, is the linguistic tool the author uses to structure narrative for the purpose of collecting event data. Relational database models make such complex data collection schemes practically feasible in a computer environment. Finally, network models are a statistical tool best suited to analyze this type of data. Driven by the metaphors of the journal (from … to) and the alchemy (words into numbers), the book leads the reader throughout a number of paths, from substantive to methodological issues, across time and disciplines: sociology, linguistics, literary criticism, history, statistics, computer science, philosophy, cognitive psychology, political science.

This book illustrates a set of tools - story grammars, relational data models, and network models - that can be profitably used for the collection, organization, and analysis of narrative data in socio-historical research. A story grammar, or Subject-Action-Object and their modifiers, is the linguistic tool the author uses to structure narrative for the purpose of collecting event data. Relational database models make such complex data collection schemes practically feasible in a computer environment. Finally, network models are a statistical tool best suited to analyze this type of data. Driven by the metaphors of the journal (from … to) and the alchemy (words into numbers), the book leads the reader throughout a number of paths, from substantive to methodological issues, across time and disciplines: sociology, linguistics, literary criticism, history, statistics, computer science, philosophy, cognitive psychology, political science.

With unique and powerful data from within a big city prison, this book clarifies the role that conversational analysis can have within a Critical Discourse Analysis perspective. In a detailed linguist

Notational analysis is used by coaches and sport scientists to gather objective data on the performance of athletes. Tactics, technique, individual athlete movement and work-rate can all be analyzed,

The allocation of limited public and private resources depends on reliable data and empirical analysis, and The Future of Philanthropy is filled with hard-to-find data, graphs, and charts, as well as

In this book, the author's strong commitment to the multi-disciplinary field of regional science emerges to provide a unifying framework between spatial modelling traditions from quantitative geograph

Large surveys are becoming increasingly available for public use, and researchers are often faced with the need to analyse complex survey data to address key scientific issues. For proper analysis it

The paradigm of deterministic chaos has influenced thinking in many fields of science. Chaotic systems show rich and surprising mathematical structures. In the applied sciences, deterministic chaos provides a striking explanation for irregular behaviour and anomalies in systems which do not seem to be inherently stochastic. The most direct link between chaos theory and the real world is the analysis of time series from real systems in terms of nonlinear dynamics. Experimental technique and data analysis have seen such dramatic progress that, by now, most fundamental properties of nonlinear dynamical systems have been observed in the laboratory. Great efforts are being made to exploit ideas from chaos theory wherever the data displays more structure than can be captured by traditional methods. Problems of this kind are typical in biology and physiology but also in geophysics, economics, and many other sciences.

Much of chemistry today relies on structural theories that look at the spatial position of atoms within molecules, but until the early 1870s such reasoning was completely unknown. Ramberg (history and

Many ecological phenomena may be modelled using apparently random processes involving space (and possibly time). Such phenomena are classified as spatial in their nature and include all aspects of pol

Disease mapping involves the analysis of geo-referenced disease incidence data and has many applications, for example within resource allocation, cluster alarm analysis, and ecological studies. There

Panel data models have become increasingly popular among applied researchers due to their heightened capacity for capturing the complexity of human behavior, as compared to cross-sectional or time ser

The theory of planar involute gearing is generalized for the design and machine-cutting of spatial involute gearing. The monograph solves a problem, which has been discussed for over 150 years. Involu

Emphasizes the strategy of experimentation, data analysis, and the interpretation of experimental results. Features numerous examples using actual engineering and scientific studies. Presents statis

Humans and other animals depend on their ability to perceive and represent spatialaspects of the world. We learn spatial schemas by observing the locations and movements of objects(including people) a

Metropolitan Governance and Spatial Planning explores the relationship between metropolitan decision-making and strategies to co-ordinate spatial policy. This relationship is examined across 20 cities

A multi-disciplinary team of authors analyze the economics of Brazilian deforestation using a large data set of ecological and economic variables. They survey the most up to date work in this field and present their own dynamic and spatial econometric analysis based on municipality level panel data spanning the entire Brazilian Amazon from 1970 to 1996. By observing the dynamics of land use change over such a long period the team is able to provide quantitative estimates of the long-run economic costs and benefits of both land clearing and government policies such as road building. The authors find that some government policies, such as road paving in already highly settled areas, are beneficial both for economic development and for the preservation of forest, while other policies, such as the construction of unpaved roads through virgin areas, stimulate wasteful land uses to the detriment of both economic growth and forest cover.

People constantly talk to each other about experience or knowledge resulting from spatial perception; they describe the size, shape, orientation and position of objects using a wide range of spatia

A goldmine of valuable tools for data modelers!Data modelers render raw data-names, addresses, and sales totals, for instance-into information such as customer profiles and seasonal buying patterns th

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

Numerical analysis is an increasingly important link between pure mathematics and its application in science and technology. This textbook provides an introduction to the justification and development of constructive methods that provide sufficiently accurate approximations to the solution of numerical problems, and the analysis of the influence that errors in data, finite-precision calculations, and approximation formulas have on results, problem formulation and the choice of method. It also serves as an introduction to scientific programming in MATLAB, including many simple and difficult, theoretical and computational exercises. A unique feature of this book is the consequent development of interval analysis as a tool for rigorous computation and computer assisted proofs, along with the traditional material.

This book describes the Bayesian approach to statistics at a level suitable for final year undergraduate and Masters students. It is unusual in presenting Bayesian statistics with a practical flavor and an emphasis on mainstream statistics, showing how to infer scientific, medical, and social conclusions from numerical data. The authors draw on many years of experience with practical and research programs and describe many statistical methods, not readily available elsewhere. A first chapter on Fisherian methods, together with a strong overall emphasis on likelihood, makes the text suitable for mainstream statistics courses whose instructors wish to follow mixed or comparative philosophies. The other chapters contain important sections relating to many areas of statistics such as the linear model, categorical data analysis, time series and forecasting, mixture models, survival analysis, Bayesian smoothing, and non-linear random effects models. The text includes a large number of practi

A guide to machine learning approaches and their application to the analysis ofbiological data.

Explores the principles and practical considerations of spatial sound recording and reproduction. Particular emphasis is given to the increasing importance of multichannel surround sound and 3D audio,

Probabilistic risk analysis aims to quantify the risk caused by high technology installations. Increasingly, such analyses are being applied to a wider class of systems in which problems such as lack of data, complexity of the systems, uncertainty about consequences, make a classical statistical analysis difficult or impossible. The authors discuss the fundamental notion of uncertainty, its relationship with probability, and the limits to the quantification of uncertainty. Drawing on extensive experience in the theory and applications of risk analysis, the authors focus on the conceptual and mathematical foundations underlying the quantification, interpretation and management of risk. They cover standard topics as well as important new subjects such as the use of expert judgement and uncertainty propagation. The relationship of risk analysis with decision making is highlighted in chapters on influence diagrams and decision theory. Finally, the difficulties of choosing metrics to quanti

An overview of the theory and application of linear and nonlinear mixed-effects models in the analysis of grouped data, such as longitudinal data, repeated measures, and multilevel data. The authors p

Structural Analysis of Historic Buildings offers the most' complete, detailed, and authentic data available on the materials, calculation methods, and design techniques used by architects and engineer

A new, revised edition of a yet unrivaled work on frequency domain analysisLong recognized for his unique focus on frequency domain methods for the analysis of time series data as well as for his appl

Student edition features: internet research, oral communication, written communication, ethical issues, technology/collaborative work, data analysis.

This book describes the Bayesian approach to statistics at a level suitable for final year undergraduate and Masters students. It is unusual in presenting Bayesian statistics with a practical flavor and an emphasis on mainstream statistics, showing how to infer scientific, medical, and social conclusions from numerical data. The authors draw on many years of experience with practical and research programs and describe many statistical methods, not readily available elsewhere. A first chapter on Fisherian methods, together with a strong overall emphasis on likelihood, makes the text suitable for mainstream statistics courses whose instructors wish to follow mixed or comparative philosophies. The other chapters contain important sections relating to many areas of statistics such as the linear model, categorical data analysis, time series and forecasting, mixture models, survival analysis, Bayesian smoothing, and non-linear random effects models. The text includes a large number of practi

This book examines the performance of Greek tragedy in the classical Athenian theatre. Whilst post structuralist criticism of Greek tragedy has tended to focus on the literary text, the analysis of stagecraft and the theatre has been markedly conservative in its methodology. David Wiles corrects that balance, exploring the performance of tragedy as a spatial practice specific to Athenian culture, at once religious and political. Athenian conceptions of space were quite unlike those of the modern world. After reviewing controversies and archaeological data regarding the fifth-century performance space, Wiles turns to the chorus and shows how dance mapped out the space for the purposes of any given play. The book shows how the performance as a whole was organised and, through informative diagrams and accessible analyses, Wiles brings the theatre of Greek tragedy to life.

Helps any serious data analyst with a computer to recognize the strengths and limitations of data, to test the assumptions implicit in the least squares methods used to fit the data, to select appropr

This book introduces business students to modern techniques of data analysis, and provides them with the commands necessary to analyze data in the statistical packages JMP and Minitab.

With applications in pattern recognition, data compression and numerical analysis, the wavelet transform is a key area of modern mathematics that brings new approaches to the analysis and synthesis of

Richard Krueger offers a rich and valuable discussion of focus group analysis that is sure to become a major guide in future focus group efforts. Analysis of focus group data is different from analysi

Morphometrics is the statistical study of biological shape and shape change. Its richest data are landmarks, points such as 'the bridge of the nose' that have biological names as well as geometric locations. This book is the first systematic survey of morphometric methods for landmark data. The methods presented here combine conventional multivariate statistical analysis with themes from plane and solid geometry and from biomathematics to support biological insights into the features of many different organs and organisms. This book will be of value to applied statisticians and geometers, as well as to all biological and biomedical researchers who need quantitative analyses of information from biomedical images.

Joe (statistics, U. of British Columbia) addresses multivariate models, statistical inference, and data analysis for multivariate non- normal response data (such as binary, ordinal, count, extreme val

This graduate-level text aims to introduce students of the natural sciences to the powerful technique of factor analysis and to provide them with the background necessary to be able to undertake analyses on their own. A thoroughly updated and expanded version of the authors' successful textbook on geological factor analysis, this book draws on examples from botany, zoology, ecology, and oceanography, as well as geology. Applied multivariate statistics has grown into a research area of almost unlimited potential in the natural sciences. The methods introduced in this book, such as classical principal components, principal component factor analysis, principal coordinate analysis, and correspondence analysis, can reduce masses of data to manageable and interpretable form. Q-mode and Q-R-mode methods are also presented. Special attention is given to methods of robust estimation and the identification of atypical and influential observations. Throughout the book, the emphasis is on applicat