Considerable attention from the international scientific community is currently focused on the wide ranging applications of wavelets. For the first time, the field's leading experts have come together to produce a complete guide to wavelet transform applications in medicine and biology. Wavelets in Medicine and Biology provides accessible, detailed, and comprehensive guidelines for all those interested in learning about wavelets and their applications to biomedical problems.

Learn shocking stats and facts that will surprise you, expand your knowledge, and help you impress your friends! Astonish yourself and your friends with Stats to Blow Your Mind & Everyone Else You're Talking To. Seeing is believing with the many intriguing charts and graphs in this book. Take your learning on the road, this book is perfect for reading during family vacations or to friends at parties. This is the perfect gift for someone who loves to learn. Spark your own curiosity with the compelling statistics in Stats to Blow Your Mind & Everyone Else You're Talking To.

Multiple Comparisons covers all-pairwise comparisons, multiple comparisons with the best, and multiple comparisons with a control. Confidence intervals methods and stepwise methods are described. Abuses and misconceptions are exposed, and the reader is guided to the correct method for each problem. Connections with bioequivalence, drug stability, and toxicity studies are discussed. Applications are illustrated with real data, analyzed by computer packages. Extension to the General Linear Model is provided.

Stochastic Finance provides an introduction to mathematical finance that is unparalleled in its accessibility. Through classroom testing, the authors have identified common pain points for students, and their approach takes great care to help the reader to overcome these difficulties and to foster understanding where comparable texts often do not. Written for advanced undergraduate students, and making use of numerous detailed examples to illustrate key concepts, this text provides all the mathematical foundations necessary to model transactions in the world of finance. A first course in probability is the only necessary background. The book begins with the discrete binomial model and the finite market model, followed by the continuous Black-Scholes model. It studies the pricing of European options by combining financial concepts such as arbitrage and self-financing trading strategies with probabilistic tools such as sigma algebras, martingales and stochastic integration. All these concepts are introduced in a relaxed and user-friendly fashion.

Suitable for anyone who enjoys logic puzzles Could be used as a companion book for a course on mathematical proof. The puzzles feature the same issues of problem-solving and proof-writing. For anyone who enjoys logical puzzles. For anyone interested in legal reasoning. For anyone who loves the game of baseball.

Insecurity is an inevitable part of being human. Although life is insecure for every organism, humans alone are burdened by knowing that this is so. This ground-breaking volume features contributions by leading international researchers exploring the social psychology of insecurity, and how existential, metaphysical and social uncertainty influence human social behaviour. Chapters in the book investigate the psychological origins of insecurity, evolutionary theorizing about the functions of insecurity, the motivational strategies people adopt to manage insecurity, self-regulation strategies, the role of insecurity in the formation and maintenance of social relationships, and the influence of insecurity and uncertainty on the organization of larger social systems and public affairs. The chapters also discuss how insecurity influences many areas of contemporary social life, highlighting the applied implications of this line of research. Topics covered include the role of insecurity in social communication, social judgments, decision making, group identification, morality, interpersonal behaviour, relationships, attitudes and many applied aspects of social life and politics where understanding the psychology of insecurity is of critical importance. This accessible and engaging book will be of interest to students, researchers and practitioners as a textbook or reference book in behavioral and social science fields, as well as to a broad spectrum of intelligent lay audience seeking to understand one of the most intriguing issues that shapes human social life.

The sequential quadratic hamiltonian (SQH) method is a novel numerical optimization procedure for solving optimal control problems governed by differential models. It is based on the characterisation of optimal controls in the framework of the Pontryagin maximum principle (PMP). The SQH method is a powerful computational methodology that is capable of development in many directions. The Sequential Quadratic Hamiltonian Method: Solving Optimal Control Problems discusses its analysis and use in solving nonsmooth ODE control problems, relaxed ODE control problems, stochastic control problems, mixed-integer control problems, PDE control problems, inverse PDE problems, differential Nash game problems, and problems related to residual neural networks. This book may serve as a textbook for undergraduate and graduate students, and as an introduction for researchers in sciences and engineering who intend to further develop the SQH method or wish to use it as a numerical tool for solving challenging optimal control problems and for investigating the Pontryagin maximum principle on new optimisation problems. Feature Provides insight into mathematical and computational issues concerning optimal control problems, while discussing many differential models of interest in different disciplines. Suitable for undergraduate and graduate students and as an introduction for researchers in sciences and engineering. Accompanied by codes which allow the reader to apply the SQH method to solve many different optimal control and optimisation problems

Model theory is the meta-mathematical study of the concept of mathematical truth. After Afred Tarski coined the term Theory of Models in the early 1950's, it rapidly became one of the central most active branches of mathematical logic. In the last few decades, ideas that originated within model theory have provided powerful tools to solve problems in a variety of areas of classical mathematics, including algebra, combinatorics, geometry, number theory, and Banach space theory and operator theory. The two volumes of Beyond First Order Model Theory present the reader with a fairly comprehensive vista, rich in width and depth, of some of the most active areas of contemporary research in model theory beyond the realm of the classical first-order viewpoint. Each chapter is intended to serve both as an introduction to a current direction in model theory and as a presentation of results that are not available elsewhere. All the articles are written so that they can be studied independently of one another. This second volume contains introductions to real-valued logic and applications, abstract elementary classes and applications, interconnections between model theory and function spaces, nonstucture theory, and model theory of second-order logic. Features A coherent introduction to current trends in model theory. Contains articles by some of the most influential logicians of the last hundred years. No other publication brings these distinguished authors together. Suitable as a reference for advanced undergraduate, postgraduates, and researchers. Material presented in the book (e.g, abstract elementary classes, first-order logics with dependent sorts, and applications of infinitary logics in set theory) is not easily accessible in the current literature. The various chapters in the book can be studied independently.

This book covers classic epidemiological designs that use a reference/control group, including case-control, case-cohort, nested case-control and variations of these designs, such as stratified and two-stage designs. It presents a unified view of these sampling designs as representations of an underlying cohort or target population of interest. This enables various extended designs to be introduced and analysed with a similar approach: extreme sampling on the outcome (extreme case-control design) or on the exposure (exposure-enriched, exposure-density, countermatched), designs that re-use prior controls and augmentation sampling designs. Further extensions exploit aggregate data for efficient cluster sampling, accommodate time-varying exposures and combine matched and unmatched controls. Self-controlled designs, including case-crossover, self-controlled case series and exposure-crossover, are also presented. The test-negative design for vaccine studies and the use of negative controls for bias assessment are introduced and discussed. This book is intended for graduate students in biostatistics, epidemiology and related disciplines, or for health researchers and data analysts interested in extending their knowledge of study design and data analysis skills. This book Bridges the gap between epidemiology and the more mathematically oriented biostatistics books. Assembles the wealth of epidemiological knowledge about observational study designs that is scattered over several decades of scientific publications. Illustrates the performance of methods in real research applications. Provides guidelines for implementation in standard software packages (Stata, R). Includes numerous exercises, covering simple mathematical proofs, consideration of proposed or published designs, and practical data analysis.

This book explores the role of listening in community engagement and peace building efforts, bridging academic research in communication and practical applications for individual and social change. For all their differences, community engagement and peacebuilding efforts share much in common: the need to establish and agree on achievable and measurable goals, the importance of trust, and the need for conflict management, to name but a few. This book presents listening-considered as a multi-disciplinary concept related to but distinct from civility, civic participation, and other social processes-as a primary mechanism for accomplishing these tasks. Individual chapters explore these themes in an array of international contexts, examining topics such as conflict resolution, restorative justice, environmental justice, migrants and refugees, and trauma-informed peacebuilding. The book includes contemporary literature reviews and theoretical insights covering the role of listening as related to individual, social, and governmental efforts to better engage communities and build, maintain, or establish peace in an increasingly divided world. This collection provides invaluable insight to researchers, students, educators, and practitioners in intercultural and international communication, conflict management, peacebuilding, community engagement, and international studies.

Handbook of Alternative Data in Finance, Volume I motivates and challenges the reader to explore and apply Alternative Data in finance. The book provides a robust and in-depth overview of Alternative Data, including its definition, characteristics, difference from conventional data, categories of Alternative Data, Alternative Data providers, and more. The book also offers a rigorous and detailed exploration of process, application and delivery that should be practically useful to researchers and practitioners alike. Features Includes cutting edge applications in machine learning, fintech, and more Suitable for professional quantitative analysts, and as a resource for postgraduates and researchers in financial mathematics Features chapters from many leading researchers and practitioners.

Evolution and the Human-Animal Drive to Conflict examines how fundamental, universal animal drives, such as dominance/prevalence, survival, kinship, and "profit" (greed, advantage, whether of material or social nature), provide the basis for 'the evolutionary trap' that promotes the unstable, conflictive, dominant-prone individual and group human behaviours. Examining this behavioural tension, the book argues that while these innate features set up behaviours that lean towards aggression influenced by social inequalities, the means implemented to defuse them resort to emotional and intellectual strategies that sponsor fanaticism and often reproduce the very same behaviours they intend to defuse. In addressing these concerns, the book argues that we should enhance our resources to promote solidarity, accept cultural differences, deter expansionist and uncontrolled profit drives, and achieve collective access towards knowledge and progress in living conditions. This entails promoting the redistribution of resources and creative labour access and avoiding policies that generate a fragmented world with collective and individual development disparities that invite and encourage dominance behaviours.This resource redistribution asserts that it is necessary to reformulate the global set of human priorities towards increased access to better living conditions, cognitive enhancement, a more amiable interaction with the ecosystem and non-aggressive cultural differences, promote universal access to knowledge and enhance creativity and cultural convivence. These behavioural changes entail partial derangement of our ancestral animal drives camouflaged under different cultural profiles until the species succeeds in replacing the dominance of basic animal drives with prosocial, collective ones. Though it entails a formidable task of confronting financial, military, and religious powers and cultural inertias - human history is also a challenging, continuous experience in these domains - for the sake of our own self-identity and self-evaluation we should reject any suggestion of not continuing embracing slowly constructing collective utopias channelled towards improving individual and collective freedom and creativeness. This book will interest academics and students in social, cognitive, and evolutionary psychology, the neurosciences, paleoanthropology, philosophy, and anthropology.

This work provides descriptions, explanations and examples of the Bayesian approach to statistics, demonstrating the utility of Bayesian methods for analyzing real-world problems in the health sciences. The work considers the individual components of Bayesian analysis.;College or university bookstores may order five or more copies at a special student price, available on request from Marcel Dekker, Inc.

This text describes regression-based approaches to analyzing longitudinal and repeated measures data. It emphasizes statistical models, discusses the relationships between different approaches, and uses real data to illustrate practical applications. It uses commercially available software when it exists and illustrates the program code and output. The data appendix provides many real data sets-beyond those used for the examples-which can serve as the basis for exercises.

Noncommutative geometry combines themes from algebra, analysis and geometry and has significant applications to physics. This book focuses on cyclic theory, and is based upon the lecture courses by Daniel G. Quillen at the University of Oxford from 1988-92, which developed his own approach to the subject. The basic definitions, examples and exercises provided here allow non-specialists and students with a background in elementary functional analysis, commutative algebra and differential geometry to get to grips with the subject. Quillen's development of cyclic theory emphasizes analogies between commutative and noncommutative theories, in which he reinterpreted classical results of Hamiltonian mechanics, operator algebras and differential graded algebras into a new formalism. In this book, cyclic theory is developed from motivating examples and background towards general results. Themes covered are relevant to current research, including homomorphisms modulo powers of ideals, traces on noncommutative differential forms, quasi-free algebras and Chern characters on connections.

In a family study of breast cancer, epidemiologists in Southern California increase the power for detecting a gene-environment interaction. In Gambia, a study helps a vaccination program reduce the incidence of Hepatitis B carriage. Archaeologists in Austria place a Bronze Age site in its true temporal location on the calendar scale. And in France, researchers map a rare disease with relatively little variation.
Each of these studies applied Markov chain Monte Carlo methods to produce more accurate and inclusive results. General state-space Markov chain theory has seen several developments that have made it both more accessible and more powerful to the general statistician. Markov Chain Monte Carlo in Practice introduces MCMC methods and their applications, providing some theoretical background as well. The authors are researchers who have made key contributions in the recent development of MCMC methodology and its application.
Considering the broad audience, the editors emphasize practice rather than theory, keeping the technical content to a minimum. The examples range from the simplest application, Gibbs sampling, to more complex applications. The first chapter contains enough information to allow the reader to start applying MCMC in a basic way. The following chapters cover main issues, important concepts and results, techniques for implementing MCMC, improving its performance, assessing model adequacy, choosing between models, and applications and their domains.
Markov Chain Monte Carlo in Practice is a thorough, clear introduction to the methodology and applications of this simple idea with enormous potential. It shows the importance of MCMC in real applications, such as archaeology, astronomy, biostatistics, genetics, epidemiology, and image analysis, and provides an excellent base for MCMC to be applied to other fields as well.

By focusing primarily on the application of structural equation modeling (SEM) techniques in example cases and situations, this book provides an understanding and working knowledge of advanced SEM techniques with a minimum of mathematical derivations. The book was written for a broad audience crossing many disciplines, assumes an understanding of graduate level multivariate statistics, including an introduction to SEM.

Many technological, socio-economic, environmental, biomedical phenomena exhibit an underlying graph structure. Valued graph allows one to incorporate the connections or links among the population units in addition. The links may provide effectively access to the part of population that is the primary target, which is the case for many unconventional sampling methods, such as indirect, network, line-intercept or adaptive cluster sampling. Or, one may be interested in the structure of the connections, in terms of the corresponding graph properties or parameters, such as when various breadth- or depth-first non-exhaustive search algorithms are applied to obtain compressed views of large often dynamic graphs. Graph sampling provides a statistical approach to study real graphs from either of these perspectives. It is based on exploring the variation over all possible sample graphs (or subgraphs) which can be taken from the given population graph, by means of the relevant known sampling probabilities. The resulting design-based inference is valid whatever the unknown properties of the given real graphs. One-of-a-kind treatise of multidisciplinary topics relevant to statistics, mathematics and data science. Probabilistic treatment of breadth-first and depth-first non-exhaustive search algorithms in graphs. Presenting cutting-edge theory and methods based on latest research. Pathfinding for future research on sampling from real graphs. Graph Sampling can primarily be used as a resource for researchers working with sampling or graph problems, and as the basis of an advanced course for post-graduate students in statistics, mathematics and data science.

Second Edition offers a comprehensive presentation of scientific sampling principles and shows how to design a sample survey and analyze the resulting data. Demonstrates the validity of theorems and statements without resorting to detailed proofs.

From imaginary numbers to the fourth dimension and beyond, mathematics has always been about imagining things that seem impossible at first glance. In x+y, Eugenia Cheng draws on the insights of higher-dimensional mathematics to reveal a transformative new way of talking about the patriarchy, mansplaining and sexism: a way that empowers all of us to make the world a better place. Using precise mathematical reasoning to uncover everything from the sexist assumptions that make society a harder place for women to live to the limitations of science and statistics in helping us understand the link between gender and society, Cheng's analysis replaces confusion with clarity, brings original thinking to well worn arguments - and provides a radical, illuminating and liberating new way of thinking about the world and women's place in it.

Structured Biological Modelling presents a straightforward introduction for computer-aided analysis, mathematical modelling, and simulation of cell biological systems. This unique guide brings together the physiological, structural, molecular biological, and theoretical aspects of the signal transduction network that regulates growth and proliferation in normal and tumor cells. It provides comprehensive survey of functional and theoretical features of intracellular signal processing and introduces the concept of cellular self-organization. Exemplified by oscillatory calcium waves, strategies for the design of computer experiments are presented that can assist or even substitute for time-consuming biological experiments. The presented minimal model for proliferation-associated signal transduction clearly shows the alterations of the cellular signal network involved in neoplastic growth. This book will be useful to cell and molecular biologists, oncologists, physiologists, theoretical biologists, computer scientists, and all other researchers and students studying functional aspects of cellular signaling.

Biology is in the midst of a era yielding many significant discoveries and promising many more. Unique to this era is the exponential growth in the size of information-packed databases. Inspired by a pressing need to analyze that data, Introduction to Computational Biology explores a new area of expertise that emerged from this fertile field- the combination of biological and information sciences.

This introduction describes the mathematical structure of biological data, especially from sequences and chromosomes. After a brief survey of molecular biology, it studies restriction maps of DNA, rough landmark maps of the underlying sequences, and clones and clone maps. It examines problems associated with reading DNA sequences and comparing sequences to finding common patterns. The author then considers that statistics of pattern counts in sequences, RNA secondary structure, and the inference of evolutionary history of related sequences.

Introduction to Computational Biology exposes the reader to the fascinating structure of biological data and explains how to treat related combinatorial and statistical problems. Written to describe mathematical formulation and development, this book helps set the stage for even more, truly interdisciplinary work in biology.

Nonlinear measurement data arise in a wide variety of biological and biomedical applications, such as longitudinal clinical trials, studies of drug kinetics and growth, and the analysis of assay and laboratory data. Nonlinear Models for Repeated Measurement Data provides the first unified development of methods and models for data of this type, with a detailed treatment of inference for the nonlinear mixed effects and its extensions. A particular strength of the book is the inclusion of several detailed case studies from the areas of population pharmacokinetics and pharmacodynamics, immunoassay and bioassay development and the analysis of growth curves.

This edition has been revised and expanded, particularly the material on rings and fields, to provide a comprehensive first course in abstract algebra. The text is written for the student encountering this subject for the first time - the treatment is clear and patient, but also provides enough depth to demonstrate the insights that abstract algebra offers. The book includes many worked examples and each chapter contains a set of graded exercises, with partial solutions.