Methods of Nonlinear Analysis

The first edition of Geometric Morphometrics for Biologists has been the primary resource for teaching modern geometric methods of shape analysis to biologists who have a stronger background in biolog

The analysis of body composition (fat, bone and muscle) is an important process throughout the biomedical sciences. This is the first book to offer a clear and detailed introduction to the key methods

The analysis of body composition (fat, bone and muscle) is an important process throughout the biomedical sciences. This is the first book to offer a clear and detailed introduction to the key methods

This book addresses researchers and practitioners interested in modeling, prediction and forecasting of natural systems based on nonlinear dynamics. It is a practical guide to data analysis and to the

What is knowledge and how is it represented? This book focuses on the idea of formalising knowledge as relations, interpreting knowledge represented in databases or logic programs as relational data and discovering new knowledge by identifying hidden and defining new relations. After a brief introduction to representational issues, the author develops a relational language for abstract machine learning problems. He then uses this language to discuss traditional methods such as clustering and decision tree induction, before moving onto two previously underestimated topics that are just coming to the fore: rough set data analysis and inductive logic programming. Its clear and precise presentation is ideal for undergraduate computer science students. The book will also interest those who study artificial intelligence or machine learning at the graduate level. Exercises are provided and each concept is introduced using the same example domain, making it easier to compare the individual pro

What is knowledge and how is it represented? This book focuses on the idea of formalising knowledge as relations, interpreting knowledge represented in databases or logic programs as relational data and discovering new knowledge by identifying hidden and defining new relations. After a brief introduction to representational issues, the author develops a relational language for abstract machine learning problems. He then uses this language to discuss traditional methods such as clustering and decision tree induction, before moving onto two previously underestimated topics that are just coming to the fore: rough set data analysis and inductive logic programming. Its clear and precise presentation is ideal for undergraduate computer science students. The book will also interest those who study artificial intelligence or machine learning at the graduate level. Exercises are provided and each concept is introduced using the same example domain, making it easier to compare the individual pro

Evidence-based medicine aims to apply the best available evidence gained from the scientific method to medical decision making. It is a practice that uses statistical analysis of scientific methods an

Frequency Domain Criteria for Absolute Stability focuses on recently-developed methods of delay-integral-quadratic constraints to provide criteria for absolute stability of nonlinear control systems.

In a number of famous works, M. Kac showed that various methods of probability theory can be fruitfully applied to important problems of analysis. The interconnection between probability and analysis

The state of migration research has undergone rapid change since methods of analysis involving stable and radiogen isotopes and molecular genetics have been started to be applied. At a conference held

Fuzzy classi?ers are important tools in exploratory data analysis, which is a vital set of methods used in various engineering, scienti?c and business applications. Fuzzy classi?ers use fuzzy rules an

Although formal analysis programming techniques may be quite old, the introduction of formal methods only dates from the 1980s. These techniques enable us to analyze the behavior of a software applica

Over the past decade, computer supported data analysis by statistical methods has been one of the fastest growth areas in chemometrics, biometrics and other related branches of natural, technical and

This book introduces in a systematic manner a general nonparametric theory of statistics on manifolds, with emphasis on manifolds of shapes. The theory has important and varied applications in medical diagnostics, image analysis, and machine vision. An early chapter of examples establishes the effectiveness of the new methods and demonstrates how they outperform their parametric counterparts. Inference is developed for both intrinsic and extrinsic Fréchet means of probability distributions on manifolds, then applied to shape spaces defined as orbits of landmarks under a Lie group of transformations - in particular, similarity, reflection similarity, affine and projective transformations. In addition, nonparametric Bayesian theory is adapted and extended to manifolds for the purposes of density estimation, regression and classification. Ideal for statisticians who analyze manifold data and wish to develop their own methodology, this book is also of interest to probabilists, mathematicia

A seminal text in European studies, which addresses issues of research design and causal analysis. The chapters draw on different methodological traditions, notions of causality, and methods and use s

Astronomy needs statistical methods to interpret data, but statistics is a many-faceted subject that is difficult for non-specialists to access. This handbook helps astronomers analyze the complex data and models of modern astronomy. This second edition has been revised to feature many more examples using Monte Carlo simulations, and now also includes Bayesian inference, Bayes factors and Markov chain Monte Carlo integration. Chapters cover basic probability, correlation analysis, hypothesis testing, Bayesian modelling, time series analysis, luminosity functions and clustering. Exercises at the end of each chapter guide readers through the techniques and tests necessary for most observational investigations. The data tables, solutions to problems, and other resources are available online at www.cambridge.org/9780521732499. Bringing together the most relevant statistical and probabilistic techniques for use in observational astronomy, this handbook is a practical manual for advanced und

Combining discourse and comparative historical methods of analysis, this book explores how colonialists and anti-colonialists renegotiated transnational power relationships within the debates on decol

This book presents recently developed statistical methods and theory required for the application of the tools of functional data analysis to problems arising in geosciences, finance, economics and bi

The interdisciplinary nature of bioinformatics presents a research challenge in integrating concepts, methods, software and multiplatform data. Although there have been rapid developments in new technology and an inundation of statistical methods for addressing other types of high-throughput data, such as proteomic profiles that arise from mass spectrometry experiments. This book discusses the development and application of Bayesian methods in the analysis of high-throughput bioinformatics data that arise from medical, in particular, cancer research, as well as molecular and structural biology. The Bayesian approach has the advantage that evidence can be easily and flexibly incorporated into statistical methods. A basic overview of the biological and technical principles behind multi-platform high-throughput experimentation is followed by expert reviews of Bayesian methodology, tools and software for single group inference, group comparisons, classification and clustering, motif discov

This book of general analytical chemistry – as opposed to instrumental analysis or separation methods – in aqueous solutions is focuses on fundamentals, which is an area too often overlooked in the li

Anthropology as a discipline is rapidly becoming more quantitative, and anthropology students are now required to develop sophisticated statistical skills. This book provides students of anthropology with a clear, step-by-step guide to univariate statistical methods, demystifying the aspects that are often seen as difficult or impenetrable. Explaining the central role of statistical methods in anthropology and using only anthropological examples, the book provides a solid footing in statistical techniques. Beginning with basic descriptive statistics, this new edition also covers more advanced methods such as analyses of frequencies and variance, simple and multiple regression analysis with dummy and continuous variables. It addresses commonly encountered problems such as small samples and non-normality. Each statistical technique is accompanied by clearly worked examples and the chapters end with practice problem sets. Many of the datasets are available for download at www.cambridge.or

• This new edition gives students valuable practice in reading and evaluating research. All major methods of research are illustrated, including qualitative research, content/document analysis, survey

This volume provides an overview of the occurrence and fate of emerging contaminants, discusses advanced chemical analysis methods, toxicological and ecotoxicological effects as well as human exposure

This book provides a thorough understanding of the concepts of optimization methods from a modern perspective at the conceptual stage of complex technical systems. It focuses on nonlinear optimization

This comprehensive text brings together in one volume the range of methods available for undertaking qualitative data collection and analysis. Qualitative Organizational Research contains 27 chapters

A systematic, unified treatment of orthogonal transform methods for signal processing, data analysis and communications, this book guides the reader from mathematical theory to problem solving in practice. It examines each transform method in depth, emphasizing the common mathematical principles and essential properties of each method in terms of signal decorrelation and energy compaction. The different forms of Fourier transform, as well as the Laplace, Z-, Walsh–Hadamard, Slant, Haar, Karhunen–Loève and wavelet transforms, are all covered, with discussion of how each transform method can be applied to real-world experimental problems. Numerous practical examples and end-of-chapter problems, supported by online Matlab and C code and an instructor-only solutions manual, make this an ideal resource for students and practitioners alike.

This book contains the products of work carried out over four decades of research in Italy, France and the United States, and in the intellectual territory between social movements, comparative politics, and historical sociology. Using a variety of methods ranging from statistical analysis to historical case studies to linguistic analysis, the book centers on historical catalogs of protest events and cycles of collective action. Sidney Tarrow places social movements in the broader arena of contentious politics, in relation to states, political parties and other actors. From peasants and communists in 1960s Italy, to movements and politics in contemporary western polities, to the global justice movement in the new century, the book argues that contentious actors are neither outside of nor completely within politics, but rather they occupy the uncertain territory between total opposition and integration into policy.

This book contains the products of work carried out over four decades of research in Italy, France and the United States, and in the intellectual territory between social movements, comparative politics, and historical sociology. Using a variety of methods ranging from statistical analysis to historical case studies to linguistic analysis, the book centers on historical catalogs of protest events and cycles of collective action. Sidney Tarrow places social movements in the broader arena of contentious politics, in relation to states, political parties and other actors. From peasants and communists in 1960s Italy, to movements and politics in contemporary western polities, to the global justice movement in the new century, the book argues that contentious actors are neither outside of nor completely within politics, but rather they occupy the uncertain territory between total opposition and integration into policy.

Measuring the performance of public agencies and programmes is essential to ensure that citizens enjoy quality services and that governments can be sure that taxpayers receive value for money. As such, good performance measurement is a crucial component of improvement and planning, monitoring and control, comparison and benchmarking and also ensures democratic accountability. This book shows how the principles, uses and practice of performance measurement for public services differ from those in for-profit organisations, being based on the need to add public value rather than profit. It describes methods and approaches for measuring performance through time, for constructing and using scorecards, composite indicators, the use of league tables and rankings and argues that data-envelopment analysis is a useful tool when thinking about performance. This demonstrates the importance of allowing for the multidimensional nature of performance, as well as the need to base measurement on a soun

Jones spent his academic career researching and teaching the relationship between soil fertility and plant nutrition, mostly at the University of Georgia, and after retirement founded a soil and plant analysis company. Here he presents material equivalent to an advanced college course, that readers with a bit of background in agronomy or chemistry can apply to specific situations, and researchers can use as reference. He covers basic principles, physical and physiochemical characteristics of soil, plant elemental requirements and associated elements, methods of assessing soil fertility and plant nutrition, amendments for soil fertility, methods for producing plants without soil, and miscellaneous topics such as organic farming and best management practices. Annotation Ac2012 Book News, Inc., Portland, OR (booknews.com)

Machine learning is an interdisciplinary field of science and engineering that studies mathematical theories and practical applications of systems that learn. This book introduces theories, methods and applications of density ratio estimation, which is a newly emerging paradigm in the machine learning community. Various machine learning problems such as non-stationarity adaptation, outlier detection, dimensionality reduction, independent component analysis, clustering, classification and conditional density estimation can be systematically solved via the estimation of probability density ratios. The authors offer a comprehensive introduction of various density ratio estimators including methods via density estimation, moment matching, probabilistic classification, density fitting and density ratio fitting, as well as describing how these can be applied to machine learning. The book provides mathematical theories for density ratio estimation including parametric and non-parametric conve

State-of-the-art analysis of geological structures has become increasingly quantitative but traditionally, graphical methods are used in teaching. This innovative lab book provides a unified methodology for problem-solving in structural geology using linear algebra and computation. Assuming only limited mathematical training, the book begins with classic orientation problems and progresses to more fundamental topics of stress, strain and error propagation. It introduces linear algebra methods as the foundation for understanding vectors and tensors, and demonstrates the application of geometry and kinematics in geoscience without requiring students to take a supplementary mathematics course. All algorithms are illustrated with a suite of online MATLAB functions, allowing users to modify the code to solve their own structural problems. Containing 20 worked examples and over 60 exercises, this is the ideal lab book for advanced undergraduates or beginning graduate students. It will also p

State-of-the-art analysis of geological structures has become increasingly quantitative but traditionally, graphical methods are used in teaching. This innovative lab book provides a unified methodology for problem-solving in structural geology using linear algebra and computation. Assuming only limited mathematical training, the book begins with classic orientation problems and progresses to more fundamental topics of stress, strain and error propagation. It introduces linear algebra methods as the foundation for understanding vectors and tensors, and demonstrates the application of geometry and kinematics in geoscience without requiring students to take a supplementary mathematics course. All algorithms are illustrated with a suite of online MATLAB functions, allowing users to modify the code to solve their own structural problems. Containing 20 worked examples and over 60 exercises, this is the ideal lab book for advanced undergraduates or beginning graduate students. It will also p

Computational experiments on algorithms can supplement theoretical analysis by showing what algorithms, implementations and speed-up methods work best for specific machines or problems. This book guides the reader through the nuts and bolts of the major experimental questions: What should I measure? What inputs should I test? How do I analyze the data? To answer these questions the book draws on ideas from algorithm design and analysis, computer systems, and statistics and data analysis. The wide-ranging discussion includes a tutorial on system clocks and CPU timers, a survey of strategies for tuning algorithms and data structures, a cookbook of methods for generating random combinatorial inputs, and a demonstration of variance reduction techniques. The book can be used by anyone who has taken a course or two in data structures and algorithms. A companion website, AlgLab (www.cs.amherst.edu/alglab) contains downloadable files, programs and tools for use in experimental projects.

Computational experiments on algorithms can supplement theoretical analysis by showing what algorithms, implementations and speed-up methods work best for specific machines or problems. This book guides the reader through the nuts and bolts of the major experimental questions: What should I measure? What inputs should I test? How do I analyze the data? To answer these questions the book draws on ideas from algorithm design and analysis, computer systems, and statistics and data analysis. The wide-ranging discussion includes a tutorial on system clocks and CPU timers, a survey of strategies for tuning algorithms and data structures, a cookbook of methods for generating random combinatorial inputs, and a demonstration of variance reduction techniques. The book can be used by anyone who has taken a course or two in data structures and algorithms. A companion website, AlgLab (www.cs.amherst.edu/alglab) contains downloadable files, programs and tools for use in experimental projects.

Originally published in 1985, this monograph describes the interaction of radiation with plasma. Using an approach that is particularly relevant to the interpretation of data from laboratory plasmas or stellar atmospheres, the author sets out the physics and mathematics of the interaction of photons with atoms, molecules, ions and electrons. The emphasis throughout is on relating the formal mathematics to the real world of observable properties and interpretation. The equation of radiative transfer for a two-level atom is solved exactly by two distinct methods. Techniques for solving more realistic problems are then presented. This leads to the main thrust of the book which gives a detailed analysis of the matter - radiation interaction.

This book provides a lucid and comprehensive introduction to the differential geometric study of partial differential equations. It was the first book to present substantial results on local solvability of general and, in particular, nonlinear PDE systems without using power series techniques. The book describes a general approach to systems of partial differential equations based on ideas developed by Lie, Cartan and Vessiot. The most basic question is that of local solvability, but the methods used also yield classifications of various families of PDE systems. The central idea is the exploitation of singular vector field systems and their first integrals. These considerations naturally lead to local Lie groups, Lie pseudogroups and the equivalence problem, all of which are covered in detail. This book will be a valuable resource for graduate students and researchers in partial differential equations, Lie groups and related fields.

This book covers the basic concepts and methods involved in polarization of light, and features important methods of analysis such as Jones matrices, Stokes parameters, and Poincare sphere. The book p

Stroock, Daniel W.: Some applications of stochastic calculus to partial differential equations.- Ikeda, Nobuyuki: Probabilistic methods in the study of asymptotics.- Nualart, David: Analysis on Wiener

Zeelander (U. of Pennsylvania) selected 38 short narratives from Genesis for this analysis of the methods used to construct endings to stories, revealing the connection of the endings to ritual in man