Matrix-analytic Methods in Stochastic Models

The globular star clusters of the Milky Way contain hundreds of thousands of stars held together by gravitational interactions, and date from the time when the Milky Way was forming. This 2003 text describes the theory astronomers need for studying globular star clusters. The gravitational million-body problem is an idealised model for understanding the dynamics of a cluster with a million stars. After introducing the million-body problem from various view-points, the book systematically develops the tools needed for studying the million-body problems in nature, and introduces the most important theoretical models. Including a comprehensive treatment of few-body interactions, and developing an intuitive but quantitative understanding of the three-body problem, the book introduces numerical methods, relevant software, and current problems. Suitable for graduate students and researchers in astrophysics and astronomy, this text also has important applications in the fields of theoretica

The globular star clusters of the Milky Way contain hundreds of thousands of stars held together by gravitational interactions, and date from the time when the Milky Way was forming. This 2003 text describes the theory astronomers need for studying globular star clusters. The gravitational million-body problem is an idealised model for understanding the dynamics of a cluster with a million stars. After introducing the million-body problem from various view-points, the book systematically develops the tools needed for studying the million-body problems in nature, and introduces the most important theoretical models. Including a comprehensive treatment of few-body interactions, and developing an intuitive but quantitative understanding of the three-body problem, the book introduces numerical methods, relevant software, and current problems. Suitable for graduate students and researchers in astrophysics and astronomy, this text also has important applications in the fields of theoretica

Offers a current analysis of mathematical methods used in the identification of models for hydrologic forecasting, design, and water resources management. The volume's 24 contributions address calibra

Facility in the targeted manipulation of the genetic and metabolic composition of organisms, combined with unprecedented computational power, is forging a niche for a new subspecialty of biotechnology called metabolic engineering. First published in 2002, this book introduces researchers and advanced students in biology and engineering to methods of optimizing biochemical systems of biotechnological relevance. It examines the development of strategies for manipulating metabolic pathways, demonstrates the need for effective systems models, and discusses their design and analysis, while placing special emphasis on optimization. The authors propose power-law models and methods of biochemical systems theory toward these ends. All concepts are derived from first principles, and the text is richly illustrated with numerous graphs and examples throughout. Special features include: nontechnical and technical introductions to models of biochemical systems; a review of basic methods of model des

In this short and very practical 2002 introduction to econometrics Philip Hans Franses guides the reader through the essential concepts of econometrics. Central to the book are practical questions in various economic disciplines, which can be answered using econometric methods and models. The book focuses on a limited number of the essential, most widely used methods, before going on to review the basics of econometrics. The book ends with a number of case studies drawn from recent empirical work to provide an intuitive illustration of what econometricians do when faced with practical questions. Throughout the book Franses emphasises the importance of specification, evaluation and implementation of models appropriate to the data. Assuming basic familiarity only with matrix algebra and calculus the book is designed to appeal as either a short stand-alone introduction for students embarking on an empirical research project or as a supplement to any standard introductory textbook.

In an age where companies and financial institutions are keenly focused on managing the financial risk of their operations, the implementation of quantitative methods and models has been of tremendous

This volume collects seven of Marc Nerlove's previously published, classic essays on panel data econometrics written over the past thirty-five years, together with a cogent essay on the history of the subject, which began with George Biddell Airey's monograph published in 1861. Since Professor Nerlove's 1966 Econometrica paper with Pietro Balestra, panel data and methods of econometric analysis appropriate to such data have become increasingly important in the discipline. The principal factors in the research environment affecting the future course of panel data econometrics are the phenomenal growth in the computational power available to the individual researcher at his or her desktop and the ready availability of data sets, both large and small, via the Internet. The best way to formulate statistical models for inference is motivated and shaped by substantive problems and understanding of the processes generating the data at hand to resolve them. The essays illustrate both the role

Emphasizing the foundations of dynamic optimization models, this book presents foundational results, concepts, methods, and tools useful in building and analyzing stochastic inventory models. Topics

This 2002 book introduces the quantum theory of gauge fields. Emphasis is placed on four non-perturbative methods: path integrals, lattice gauge theories, the 1/N expansion, and reduced matrix models, all of which have important contemporary applications. Written as a textbook, it assumes a knowledge of quantum mechanics and elements of perturbation theory, while many relevant concepts are pedagogically introduced at a basic level in the first half of the book. The second half comprehensively covers large-N Yang-Mills theory. The book uses an approach to gauge theories based on path-dependent phase factors known as the Wilson loops, and contains problems with detailed solutions to aid understanding. Suitable for advanced graduate courses in quantum field theory, the book will also be of interest to researchers in high energy theory and condensed matter physics as a survey of recent developments in gauge theory.

Finance provides a dramatic example of the successful application of advanced mathematical techniques to the practical problem of pricing financial derivatives. This self-contained 2002 text is designed for first courses in financial calculus aimed at students with a good background in mathematics. Key concepts such as martingales and change of measure are introduced in the discrete time framework, allowing an accessible account of Brownian motion and stochastic calculus: proofs in the continuous-time world follow naturally. The Black-Scholes pricing formula is first derived in the simplest financial context. The second half of the book is then devoted to increasing the financial sophistication of the models and instruments. The final chapter introduces more advanced topics including stock price models with jumps, and stochastic volatility. A valuable feature is the large number of exercises and examples, designed to test technique and illustrate how the methods and concepts can be app

Finance provides a dramatic example of the successful application of advanced mathematical techniques to the practical problem of pricing financial derivatives. This self-contained 2002 text is designed for first courses in financial calculus aimed at students with a good background in mathematics. Key concepts such as martingales and change of measure are introduced in the discrete time framework, allowing an accessible account of Brownian motion and stochastic calculus: proofs in the continuous-time world follow naturally. The Black-Scholes pricing formula is first derived in the simplest financial context. The second half of the book is then devoted to increasing the financial sophistication of the models and instruments. The final chapter introduces more advanced topics including stock price models with jumps, and stochastic volatility. A valuable feature is the large number of exercises and examples, designed to test technique and illustrate how the methods and concepts can be app

The second edition of this book is unique in that it focuses on methods for making formal statistical inference from all the models in an a priori set (Multi-Model Inference). A philosophy is presente

Covering sex allocation, sex determination and operational sex ratios, this multi-author volume provides both a conceptual context and an instruction in methods for many aspects of sex ratio research. Theory, statistical analysis and genetics are each explained and discussed in the first three sections. The remaining chapters each focus on research in one of a wide spectrum of animal, plant and microbial taxa, including sex ratio distorting bacteria in invertebrates, malarial parasites, birds, human and other mammals, giving critical appraisals of such research. Sex Ratios: Concepts and Research Methods is primarily intended for graduate and professional behavioural and evolutionary ecologists in this field, but it will also be useful to biologists building evolutionary models, and researchers analysing data involving proportions or comparisons across phylogenetically related species.

Covering sex allocation, sex determination and operational sex ratios, this multi-author volume provides both a conceptual context and an instruction in methods for many aspects of sex ratio research. Theory, statistical analysis and genetics are each explained and discussed in the first three sections. The remaining chapters each focus on research in one of a wide spectrum of animal, plant and microbial taxa, including sex ratio distorting bacteria in invertebrates, malarial parasites, birds, human and other mammals, giving critical appraisals of such research. Sex Ratios: Concepts and Research Methods is primarily intended for graduate and professional behavioural and evolutionary ecologists in this field, but it will also be useful to biologists building evolutionary models, and researchers analysing data involving proportions or comparisons across phylogenetically related species.

Certain interactions, such as nuclear forces and the forces of 'high-energy' physics, which arise in the theory of elementary particles, cannot be described successfully by quantum field theory. Considerable interest has therefore centred on attempts to formulate interactions between elementary particles in terms of the S-Matrix, an operator introduced by Heisenberg which connects the input and output of a scattering experiment without seeking to give a localized description of the intervening events. In this book four authors, who are together responsible for many of these developments, set out a theory of the S-Matrix starting, as far as possible, from physically plausible assumptions and investigate the mathematical consequences. The least understood of these assumptions is the vital postulate of analyticity; much insight can however be gained into its working by a study of the Feyman integrals and the book describes what is known about their analytic and high energy properties. Ori

This second volume includes research contributions on the use of dynamical systems and stochastic models in disease dynamics. Graduate students in applied mathematics, scientists in the natural, soci

This book presents a cogent description of the main methodologies used in derivatives pricing. Starting with a summary of the elements of Stochastic Calculus, Quantitative Methods in Derivatives Prici

An essential textbook for any student or researcher in biology needing to design experiments, sample programs or analyse the resulting data. The text begins with a revision of estimation and hypothesis testing methods, covering both classical and Bayesian philosophies, before advancing to the analysis of linear and generalized linear models. Topics covered include linear and logistic regression, simple and complex ANOVA models (for factorial, nested, block, split-plot and repeated measures and covariance designs), and log-linear models. Multivariate techniques, including classification and ordination, are then introduced. Special emphasis is placed on checking assumptions, exploratory data analysis and presentation of results. The main analyses are illustrated with many examples from published papers and there is an extensive reference list to both the statistical and biological literature. The book is supported by a website that provides all data sets, questions for each chapter and l

Hepatitis C infects 170 million people worldwide, and has been labelled the 'silent epidemic' as a result of its concealed attack on the liver. This multidisciplinary overview covers basic concepts related to the discovery of the virus, development of serological and nucleic acid tests to detect infection, the structure of the virus genome, generation of virus gene products, and proposed replication scheme. It then goes on to introduce the epidemiology, transmission, pathogenesis of infection, the development of hepatocellular carcinoma associated with chronic virus infection, and current strategies for treatment. The book then discusses advances in cell culture systems, animal models of infection, and emerging treatments and vaccine development. Through its coverage of basic science, clinical consequences, and methods of research, this integrated and accessible account will be of immense value to biomedical scientists and clinicians alike, and a useful introduction for all those study

The third edition of this successful textbook is fully updated and includes important recent developments in cosmology. It begins with an introduction to cosmology and general relativity, and goes on to cover the mathematical models of standard cosmology. The physical aspects of cosmology, including primordial nucleosynthesis, the astroparticle physics of inflation, and the current ideas on structure formation are discussed. Alternative models of cosmology are reviewed, including the model of Quasi-Steady State Cosmology, which has recently been proposed as an alternative to Big Bang Cosmology. The final chapters discuss observational cosmology, and debate theory versus observational methods. The book includes 400 problems and numerous worked examples. This introductory textbook describes modern cosmology at a level suitable for advanced undergraduates and graduates who are familiar with mathematical methods and basic theoretical physics. It is intended for use on courses in theoretic

This 2002 book presents the reader with mathematical tools taken from matrix calculus and zero-one matrices and demonstrates how these tools greatly facilitate the application of classical statistical procedures to econometric models. The matrix calculus results are derived from a few basic rules that are generalizations of the rules of ordinary calculus. These results are summarized in a useful table. Well-known zero-one matrices, together with some newer ones, are defined, their mathematical roles explained, and their useful properties presented. The basic building blocks of classical statistics, namely the score vector, the information matrix, and the Cramer-Rao lower bound, are obtained for a sequence of linear econometric models of increasing statistical complexity. From these are obtained interactive interpretations of maximum likelihood estimators, linking them with efficient econometric estimators. Classical test statistics are also derived and compared for hypotheses of intere

Almost every artifact in archaeological analysis originates in or on the ground. While there are elaborate methods for extracting and analyzing artifacts, treatment of the matrix within which they are

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

Statistics do not lie, nor is probability paradoxical. You just have to have the right intuition. In this lively look at both subjects, David Williams convinces mathematics students of the intrinsic interest of statistics and probability, and statistics students that the language of mathematics can bring real insight and clarity to their subject. He helps students build the intuition needed, in a presentation enriched with examples drawn from all manner of applications, e.g., genetics, filtering, the Black–Scholes option-pricing formula, quantum probability and computing, and classical and modern statistical models. Statistics chapters present both the Frequentist and Bayesian approaches, emphasising Confidence Intervals rather than Hypothesis Test, and include Gibbs-sampling techniques for the practical implementation of Bayesian methods. A central chapter gives the theory of Linear Regression and ANOVA, and explains how MCMC methods allow greater flexibility in modelling. C or WinBUG

Statistics do not lie, nor is probability paradoxical. You just have to have the right intuition. In this lively look at both subjects, David Williams convinces mathematics students of the intrinsic interest of statistics and probability, and statistics students that the language of mathematics can bring real insight and clarity to their subject. He helps students build the intuition needed, in a presentation enriched with examples drawn from all manner of applications, e.g., genetics, filtering, the Black–Scholes option-pricing formula, quantum probability and computing, and classical and modern statistical models. Statistics chapters present both the Frequentist and Bayesian approaches, emphasising Confidence Intervals rather than Hypothesis Test, and include Gibbs-sampling techniques for the practical implementation of Bayesian methods. A central chapter gives the theory of Linear Regression and ANOVA, and explains how MCMC methods allow greater flexibility in modelling. C or WinBUG

Kot (applied mathematics, U. of Washington) presents an introductory text on the methods of classical and mathematical models and methods in population ecology. Covering density dependence, bifurcatio

This book provides a thorough and self-contained study of interdependence and complexity in settings of functional analysis, harmonic analysis and stochastic analysis. It focuses on 'dimension' as a basic counter of degrees of freedom, leading to precise relations between combinatorial measurements and various indices originating from the classical inequalities of Khintchin, Littlewood and Grothendieck. The basic concepts of fractional Cartesian products and combinatorial dimension are introduced and linked to scales calibrated by harmonic-analytic and stochastic measurements. Topics include the (two-dimensional) Grothendieck inequality and its extensions to higher dimensions, stochastic models of Brownian motion, degrees of randomness and Frechet measures in stochastic analysis. This book is primarily aimed at graduate students specialising in harmonic analysis, functional analysis or probability theory. It contains many exercises and is suitable to be used as a textbook. It is also o

Elements of Mathematical Ecology provides an introduction to classical and modern mathematical models, methods, and issues in population ecology. The first part of the book is devoted to simple, unstructured population models that ignore much of the variability found in natural populations for the sake of tractability. Topics covered include density dependence, bifurcations, demographic stochasticity, time delays, population interactions (predation, competition, and mutualism), and the application of optimal control theory to the management of renewable resources. The second part of this book is devoted to structured population models, covering spatially-structured population models (with a focus on reaction-diffusion models), age-structured models, and two-sex models. Suitable for upper level students and beginning researchers in ecology, mathematical biology and applied mathematics, the volume includes numerous clear line diagrams that clarify the mathematics, relevant problems thou

This general introduction to the ideas and techniques required for the mathematical modelling of diseases begins with an outline of some disease statistics dating from Daniel Bernoulli's 1760 smallpox data. The authors then describe simple deterministic and stochastic models in continuous and discrete time for epidemics taking place in either homogeneous or stratified (non-homogeneous) populations. Several techniques for constructing and analysing models are provided, mostly in the context of viral and bacterial diseases of human populations. These models are contrasted with models for rumours and vector-borne diseases like malaria. Questions of fitting data to models, and their use in understanding methods for controlling the spread of infection, are discussed. Exercises and complementary results at the end of each chapter extend the scope of the text, which will be useful for students taking courses in mathematical biology who have some basic knowledge of probability and statistics.

Eric Ghysels and Denise R. Osborn provide a thorough and timely review of the recent developments in the econometric analysis of seasonal economic time series, summarizing a decade of theoretical advances in the area. The authors discuss the asymptotic distribution theory for linear nonstationary seasonal stochastic processes. They also cover the latest contributions to the theory and practice of seasonal adjustment, together with its implications for estimation and hypothesis testing. Moreover, a comprehensive analysis of periodic models is provided, including stationary and nonstationary cases. The book concludes with a discussion of some nonlinear seasonal and periodic models. The treatment is designed for an audience of researchers and advanced graduate students.

Eric Ghysels and Denise R. Osborn provide a thorough and timely review of the recent developments in the econometric analysis of seasonal economic time series, summarizing a decade of theoretical advances in the area. The authors discuss the asymptotic distribution theory for linear nonstationary seasonal stochastic processes. They also cover the latest contributions to the theory and practice of seasonal adjustment, together with its implications for estimation and hypothesis testing. Moreover, a comprehensive analysis of periodic models is provided, including stationary and nonstationary cases. The book concludes with a discussion of some nonlinear seasonal and periodic models. The treatment is designed for an audience of researchers and advanced graduate students.

Random matrices arise from, and have important applications to, number theory, probability, combinatorics, representation theory, quantum mechanics, solid state physics, quantum field theory, quantum gravity, and many other areas of physics and mathematics. This 2001 volume of surveys and research results, based largely on lectures given at the Spring 1999 MSRI program of the same name, covers broad areas such as topologic and combinatorial aspects of random matrix theory; scaling limits, universalities and phase transitions in matrix models; universalities for random polynomials; and applications to integrable systems. Its stress on the interaction between physics and mathematics will make it a welcome addition to the shelves of graduate students and researchers in both fields, as will its expository emphasis.

A collection of articles written by mathematicians and physicists, designed to describe the state of the art in climate models with stochastic input. Mathematicians will benefit from a survey of simpl

This book, first published in 2001, explores two shifts in the paradigms of governance in Western bureaucracies. They are the widespread use of privatisation, private firms and market methods to run core public services, and the conscious attempt to transform the role of citizenship from ideals of entitlement and security to notions of mutual obligation, selectivity and risk. Considine examines the most important service of the modern welfare state - unemployment assistance - to explain and theorise the nature of these radical changes. He undertakes research in the United Kingdom, the Netherlands, Australia and New Zealand, four countries which have been among the boldest reformers within the OECD, yet each adopting different models. Each case is a break from the standards of responsible democracy and legal-rational bureaucracy, with at least one government opting for a commercial paradigm based on targets and economic incentives and another opting for a model based on network governan

Twenty-one contributions from scholars of education present models of developmental education programs in higher education. The models consist of methods and techniques for implementing developmental

Independent Component Analysis (ICA) has recently become an important tool for modelling and understanding empirical datasets. It is a method of separating out independent sources from linearly mixed data, and belongs to the class of general linear models. ICA provides a better decomposition than other well-known models such as principal component analysis. This self-contained book contains a structured series of edited papers by leading researchers in the field, including an extensive introduction to ICA. The major theoretical bases are reviewed from a modern perspective, current developments are surveyed and many case studies of applications are described in detail. The latter include biomedical examples, signal and image denoising and mobile communications. ICA is discussed in the framework of general linear models, but also in comparison with other paradigms such as neural network and graphical modelling methods. The book is ideal for researchers and graduate students in the field.

Because of their intuitive layout, extensive mathematical capabilities, and convenient graphics, spreadsheets provide an easy, straightforward route to scientific computing. This textbook for undergraduate and entry-level graduate chemistry and chemical engineering students uses Excel, the most powerful available spreadsheet, to explore and solve problems in general and chemical data analysis. This is the only up-to-date text on the use of spreadsheets in chemistry. The book discusses topics including statistics, chemical equilibria, pH calculations, titrations, and instrumental methods such as chromatography, spectrometry, and electroanalysis. It contains many examples of data analysis, and uses spreadsheets for numerical simulations, and testing analytical procedures. It also treats modern data analysis methods such as linear and non-linear least squares in great detail, as well as methods based on Fourier transformation. The book shows how matrix methods can be powerful tools in dat

Because of their intuitive layout, extensive mathematical capabilities, and convenient graphics, spreadsheets provide an easy, straightforward route to scientific computing. This textbook for undergraduate and entry-level graduate chemistry and chemical engineering students uses Excel, the most powerful available spreadsheet, to explore and solve problems in general and chemical data analysis. This is the only up-to-date text on the use of spreadsheets in chemistry. The book discusses topics including statistics, chemical equilibria, pH calculations, titrations, and instrumental methods such as chromatography, spectrometry, and electroanalysis. It contains many examples of data analysis, and uses spreadsheets for numerical simulations, and testing analytical procedures. It also treats modern data analysis methods such as linear and non-linear least squares in great detail, as well as methods based on Fourier transformation. The book shows how matrix methods can be powerful tools in dat

This collection brings together important contributions by leading econometricians on (i) parametric approaches to qualitative and sample selection models, (ii) nonparametric and semi-parametric approaches to qualitative and sample selection models, and (iii) nonlinear estimation of cross-sectional and time series models. The advances achieved here can have important bearing on the choice of methods and analytical techniques in applied research.

Optimal Reliability Design, first published in 2000, provides a detailed introduction to systems reliability and reliability optimization. Techniques for maximizing system reliability are described, focusing on component reliability enhancement and redundancy arrangement. The authors present several case studies and show how optimization techniques are applied in practice. They also pay particular attention to finding methods that give the optimal trade-off between reliability and cost. The book begins with a review of key background material, and a discussion of a range of optimization models. The authors go on to cover optimization tools, such as heuristics, discrete optimization, nonlinear programming, mixed integer programming, optimal arrangement, and metaheuristic algorithms. They also describe the computational implementation of these tools. Many numerical examples are included, and the book contains over 180 homework exercises. It is suitable as a textbook for graduate-level co