Complex Data Modeling and Computationally Intensive Statistical Methods

Multivariate methods are employed widely in the analysis of experimental data but are poorly understood by those users who are not statisticians. This is because of the wide divergence between the theory and practice of multivariate methods. This book provides concise yet thorough surveys of developments in multivariate statistical analysis and gives statistically sound coverage of the subject. The contributors are all experienced in the theory and practice of multivariate methods and their aim has been to emphasize the major features from the point of view of applicability and to indicate the limitations and conditions of the techniques. Professional statisticians wanting to improve their background in applicable methods, users of high-level statistical methods wanting to improve their background in fundamentals, and graduate students of statistics will all find this volume of value and use.

This book summarizes all new data obtained after development of methods of Golgi complex sub fractionation, molecular biology and microscopy. It collects the full range of expertise, different points

Given a data set, you can fit thousands of models at the push of a button, but how do you choose the best? With so many candidate models, overfitting is a real danger. Is the monkey who typed Hamlet actually a good writer? Choosing a model is central to all statistical work with data. We have seen rapid advances in model fitting and in the theoretical understanding of model selection, yet this book is the first to synthesize research and practice from this active field. Model choice criteria are explained, discussed and compared, including the AIC, BIC, DIC and FIC. The uncertainties involved with model selection are tackled, with discussions of frequentist and Bayesian methods; model averaging schemes are presented. Real-data examples are complemented by derivations providing deeper insight into the methodology, and instructive exercises build familiarity with the methods. The companion website features Data sets and R code.

Monitoring Ecological Impacts provides the tools needed by professional ecologists, scientists, engineers, planners and managers to design assessment programs that can reliably monitor, detect and allow management of human impacts on the natural environment. The procedures described are well grounded in inferential logic, and the statistical models needed to analyse complex data are given. Step-by-step guidelines and flow diagrams provide the reader with clear and useable protocols, which can be applied in any region of the world and to a wide range of human impacts. In addition, real examples are used to show how the theory can be put into practice. Although the context of this book is flowing water environments, especially rivers and streams, the advice for designing assessment programs can be applied to any ecosystem.

Continuing to emphasize numerical and graphical methods, An Introduction to Generalized Linear Models, Third Edition provides a cohesive framework for statistical modeling. This new edition of a bests

This practical guide to survival data and its analysis for readers with a minimal background in statistics shows why the analytic methods work and how to effectively analyze and interpret epidemiologic and medical survival data with the help of modern computer systems. The introduction presents a review of a variety of statistical methods that are not only key elements of survival analysis but are also central to statistical analysis in general. Techniques such as statistical tests, transformations, confidence intervals, and analytic modeling are presented in the context of survival data but are, in fact, statistical tools that apply to understanding the analysis of many kinds of data. Similarly, discussions of such statistical concepts as bias, confounding, independence, and interaction are presented in the context of survival analysis and also are basic components of a broad range of applications. These topics make up essentially a 'second-year', one-semester biostatistics course in

This practical guide to survival data and its analysis for readers with a minimal background in statistics shows why the analytic methods work and how to effectively analyze and interpret epidemiologic and medical survival data with the help of modern computer systems. The introduction presents a review of a variety of statistical methods that are not only key elements of survival analysis but are also central to statistical analysis in general. Techniques such as statistical tests, transformations, confidence intervals, and analytic modeling are presented in the context of survival data but are, in fact, statistical tools that apply to understanding the analysis of many kinds of data. Similarly, discussions of such statistical concepts as bias, confounding, independence, and interaction are presented in the context of survival analysis and also are basic components of a broad range of applications. These topics make up essentially a 'second-year', one-semester biostatistics course in

With a focus on analyzing and modeling linear dynamic systems using statistical methods, Time Series Analysis formulates various linear models, discusses their theoretical characteristics, and explore

This book studies the formation of complex societies in prehistoric China during the Neolithic and early state periods, c. 7000–1500 BC. Archaeological materials are interpreted through anthropological perspectives, using systematic analytic methods in settlement and burial patterns. Both agency and process are considered in the development of chiefdoms and in the emergence of early states in the Yellow River region. Interrelationships between factors such as mortuary practice, craft specialization, ritual activities, warfare, exchange of elite goods, climatic fluctuations, and environmental changes are emphasized. This study offers a critical evaluation of current archaeological data from Chinese sources, and argues that, although some general tendencies are noted, social changes were affected by multiple factors in no pre-determined sequence. In this most comprehensive study to date, Li Liu attempts to reconstruct developmental trajectories toward early states in Chinese civilization

This book concerns the use of concepts from statistical physics in the description of financial systems. The authors illustrate the scaling concepts used in probability theory, critical phenomena, and fully developed turbulent fluids. These concepts are then applied to financial time series. The authors also present a stochastic model that displays several of the statistical properties observed in empirical data. Statistical physics concepts such as stochastic dynamics, short- and long-range correlations, self-similarity and scaling permit an understanding of the global behaviour of economic systems without first having to work out a detailed microscopic description of the system. Physicists will find the application of statistical physics concepts to economic systems interesting. Economists and workers in the financial world will find useful the presentation of empirical analysis methods and well-formulated theoretical tools that might help describe systems composed of a huge number o

Modern statistical methods use complex, sophisticated models that can lead to intractable computations. Saddlepoint approximations can be the answer. Written from the user's point of view, this book explains in clear language how such approximate probability computations are made, taking readers from the very beginnings to current applications. The core material is presented in chapters 1-6 at an elementary mathematical level. Chapters 7-9 then give a highly readable account of higher-order asymptotic inference. Later chapters address areas where saddlepoint methods have had substantial impact: multivariate testing, stochastic systems and applied probability, bootstrap implementation in the transform domain, and Bayesian computation and inference. No previous background in the area is required. Data examples from real applications demonstrate the practical value of the methods. Ideal for graduate students and researchers in statistics, biostatistics, electrical engineering, econometric

Phase diagrams are used in materials research and engineering to understand the interrelationship between composition, microstructure and process conditions. In complex systems, computational methods such as CALPHAD are employed to model thermodynamic properties for each phase and simulate multicomponent phase behavior. Written by recognized experts in the field, this is an introductory guide to the CALPHAD method, providing a theoretical and practical approach. Building on core thermodynamic principles, this 2007 book applies crystallography, first principles methods and experimental data to computational phase behavior modeling using the CALPHAD method. With a chapter dedicated to creating thermodynamic databases, the reader will be confident in assessing, optimizing and validating complex thermodynamic systems alongside database construction and manipulation. Several case studies put the methods into a practical context, making this suitable for use on advanced materials design and

Model order reduction (MOR) techniques reduce the complexity of VLSI designs, paving the way to higher operating speeds and smaller feature sizes. This book presents a systematic introduction to, and treatment of, the key MOR methods employed in general linear circuits, using real-world examples to illustrate the advantages and disadvantages of each algorithm. Following a review of traditional projection-based techniques, coverage progresses to more advanced MOR methods for VLSI design, including HMOR, passive truncated balanced realization (TBR) methods, efficient inductance modeling via the VPEC model, and structure-preserving MOR techniques. Where possible, numerical methods are approached from the CAD engineer's perspective, avoiding complex mathematics and allowing the reader to take on real design problems and develop more effective tools. With practical examples and over 100 illustrations, this book is suitable for researchers and graduate students of electrical and computer eng

Written by a group of international experts in their field, this book is a review of Lagrangian observation, analysis and assimilation methods in physical and biological oceanography. This multidisciplinary text presents new results on nonlinear analysis of Lagrangian dynamics, the prediction of particle trajectories, and Lagrangian stochastic models. It includes historical information, up-to-date developments, and speculation on future developments in Lagrangian-based observations, analysis, and modeling of physical and biological systems. Containing contributions from experimentalists, theoreticians, and modelers in the fields of physical oceanography, marine biology, mathematics, and meteorology, this book will be of great interest to researchers and graduate students looking for both practical applications and information on the theory of transport and dispersion in physical systems, biological modeling, and data assimilation.

Filtering and system identification are powerful techniques for building models of complex systems. This 2007 book discusses the design of reliable numerical methods to retrieve missing information in models derived using these techniques. Emphasis is on the least squares approach as applied to the linear state-space model, and problems of increasing complexity are analyzed and solved within this framework, starting with the Kalman filter and concluding with the estimation of a full model, noise statistics and state estimator directly from the data. Key background topics, including linear matrix algebra and linear system theory, are covered, followed by different estimation and identification methods in the state-space model. With end-of-chapter exercises, MATLAB simulations and numerous illustrations, this book will appeal to graduate students and researchers in electrical, mechanical and aerospace engineering. It is also useful for practitioners. Additional resources for this title,

This book examines the economic bases of regional sovereignty movements in the Russian Federation from 1990–1993. The analysis is based on an original data set of Russian regional sovereignty movements and the author employs a variety of methods including quantitative statistical analysis, as well as qualitative case studies of Sverdlovsk and Samara oblasts using systematic content analysis of local newspaper articles. The central finding of the book is that variation in Russian regional activism is explained not by differences in economic conditions but by differences in the construction or imagination of economic interests; to put it in the language of other contemporary debates, economic advantage and disadvantage are as imagined as nations. In arguing that regional economic interests are inter-subjective, contingent, and institutionally specific, the book addresses a major question in political economy, namely the origin of economic interests. In addition, by engaging the national

The small sample properties of estimators and tests are frequently too complex to be useful or are unknown. Much econometric theory is therefore developed for very large or asymptotic samples where it is assumed that the behaviour of estimators and tests will adequately represent their properties in small samples. Refined asymptotic methods adopt an intermediate position by providing improved approximations to small sample behaviour using asymptotic expansions. Dedicated to the memory of Michael Magdalinos, whose work is a major contribution to this area, this book contains chapters directly concerned with refined asymptotic methods. In addition, there are chapters focusing on new asymptotic results; the exploration through simulation of the small sample behaviour of estimators and tests in panel data models; and improvements in methodology. With contributions from leading econometricians, this collection will be essential reading for researchers and graduate students concerned with th

Where did SARS come from? Have we inherited genes from Neanderthals? How do plants use their internal clock? The genomic revolution in biology enables us to answer such questions. But the revolution would have been impossible without the support of powerful computational and statistical methods that enable us to exploit genomic data. Many universities are introducing courses to train the next generation of bioinformaticians: biologists fluent in mathematics and computer science, and data analysts familiar with biology. This readable and entertaining book, based on successful taught courses, provides a roadmap to navigate entry to this field. It guides the reader through key achievements of bioinformatics, using a hands-on approach. Statistical sequence analysis, sequence alignment, hidden Markov models, gene and motif finding and more, are introduced in a rigorous yet accessible way. A companion website provides the reader with Matlab-related software tools for reproducing the steps de

Advances in experimental methods have resulted in the generation of enormous volumes of data across the life sciences. Hence clustering and classification techniques that were once predominantly the domain of ecologists are now being used more widely. This 2006 book provides an overview of these important data analysis methods, from long-established statistical methods to more recent machine learning techniques. It aims to provide a framework that will enable the reader to recognise the assumptions and constraints that are implicit in all such techniques. Important generic issues are discussed first and then the major families of algorithms are described. Throughout the focus is on explanation and understanding and readers are directed to other resources that provide additional mathematical rigour when it is required. Examples taken from across the whole of biology, including bioinformatics, are provided throughout the book to illustrate the key concepts and each technique's potential.

fMRI is a very popular method for researchers and clinicians to image human brain activity in response to given mental tasks. This book presents a comprehensive review of the methods for computing activity maps, while providing an intuitive and mathematical outline of how each method works. The approaches include statistical parametric maps (SPM), hemodynamic response modeling and deconvolution, Bayesian, Fourier and nonparametric methods. The newest activity maps provide information on regional connectivity and include principal and independent component analysis, crisp and fuzzy clustering, structural equation modeling, and dynamic causal modeling. Preprocessing and experimental design issues are discussed with references made to the software available for implementing the various methods. Aimed at graduate students and researchers, it will appeal to anyone with an interest in fMRI and who is looking to expand their perspectives of this technique.

This book collects and unifies statistical models and methods that have been proposed for analyzing interval-censored failure time data. It provides the first comprehensive coverage of the topic of in

The long-awaited second edition of this well-received textbook gives a thorough introduction to observational astronomy. Starting with the basics of positional astronomy and systems of time, it continues with charts and catalogs covering both historically important publications and modern electronic databases. The book builds on a fundamental discussion of the basics of light and the effects of the atmosphere on astronomical observations. Chapters include discussions of optical telescopes, detectors, photometry, variable stars, astrometry, spectroscopy, and solar observations. This edition contains new discussions of measurements with CCDs and appendices give basic statistical methods, useful astronomical software and websites, and sources of accurate time-calibration signals. Observational Astronomy is the perfect textbook for upper level undergraduate or beginning graduate courses on astronomy. Examples based on real astronomical data are placed throughout the text. Each of the well-

The problems of making inferences about the natural world from noisy observations and imperfect theories occur in almost all scientific disciplines. This 2006 book addresses these problems using examples taken from geophysical fluid dynamics. It focuses on discrete formulations, both static and time-varying, known variously as inverse, state estimation or data assimilation problems. Starting with fundamental algebraic and statistical ideas, the book guides the reader through a range of inference tools including the singular value decomposition, Gauss-Markov and minimum variance estimates, Kalman filters and related smoothers, and adjoint (Lagrange multiplier) methods. The final chapters discuss a variety of practical applications to geophysical flow problems. Discrete Inverse and State Estimation Problems is an ideal introduction to the topic for graduate students and researchers in oceanography, meteorology, climate dynamics, and geophysical fluid dynamics. It is also accessible to a

Demography in Archaeology, first published in 2006, is a review of current theory and method in the reconstruction of populations from archaeological data. Starting with a summary of demographic concepts and methods, the book examines historical and ethnographic sources of demographic evidence before addressing the methods by which reliable demographic estimates can be made from skeletal remains, settlement evidence and modern and ancient biomolecules. Recent debates in palaeodemography are evaluated, new statistical methods for palaeodemographic reconstruction are explained, and the notion that past demographic structures and processes were substantially different from those pertaining today is critiqued. The book covers a wide span of evidence, from the evolutionary background of human demography to the influence of natural and human-induced catastrophes on population growth and survival. This is essential reading for any archaeologist or anthropologist with an interest in relating t

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

A precise and accessible presentation of linear model theory, illustrated with data examplesStatisticians often use linear models for data analysis and for developing new statistical methods. Most boo

Demography in Archaeology, first published in 2006, is a review of current theory and method in the reconstruction of populations from archaeological data. Starting with a summary of demographic concepts and methods, the book examines historical and ethnographic sources of demographic evidence before addressing the methods by which reliable demographic estimates can be made from skeletal remains, settlement evidence and modern and ancient biomolecules. Recent debates in palaeodemography are evaluated, new statistical methods for palaeodemographic reconstruction are explained, and the notion that past demographic structures and processes were substantially different from those pertaining today is critiqued. The book covers a wide span of evidence, from the evolutionary background of human demography to the influence of natural and human-induced catastrophes on population growth and survival. This is essential reading for any archaeologist or anthropologist with an interest in relating t

Geographical Information Systems has moved from the domain of the computer specialist into the wider archaeological community, providing it with an exciting new research method. This clearly written but rigorous book provides a comprehensive guide to that use. Topics covered include: the theoretical context and the basics of GIS; data acquisition including database design; interpolation of elevation models; exploratory data analysis including spatial queries; statistical spatial analysis; map algebra; spatial operations including the calculation of slope and aspect, filtering and erosion modeling; methods for analysing regions; visibility analysis; network analysis including hydrological modeling; the production of high quality output for paper and electronic publication; and the use and production of metadata. Offering an extensive range of archaeological examples, it is an invaluable source of practical information for all archaeologists, whether engaged in cultural resource manageme

Legal and public policies concerning youth gun violence tend to rely heavily on crime reports, survey data, and statistical methods. Rarely is attention given to the young voices belonging to those wh

Legal and public policies concerning youth gun violence tend to rely heavily on crime reports, survey data, and statistical methods. Rarely is attention given to the young voices belonging to those wh

The advent of fiber optic transmission systems and wavelength division multiplexing (WDM) have led to a dramatic increase in the usable bandwidth of single fiber systems. This book provides detailed coverage of survivability (dealing with the risk of losing large volumes of traffic data due to a failure of a node or a single fiber span) and traffic grooming (managing the increased complexity of smaller user requests over high capacity data pipes), both of which are key issues in modern optical networks. A framework is developed to deal with these problems in wide-area networks, where the topology used to service various high-bandwidth (but still small in relation to the capacity of the fiber) systems evolves toward making use of a general mesh. Effective solutions, exploiting complex optimization techniques, and heuristic methods are presented to keep network problems tractable. Newer networking technologies and efficient design methodologies are also described.

This graduate/research level text introduces the theory of multi-electron transitions in atomic, molecular and optical physics, emphasising the emerging topic of dynamic electron correlation. The book begins with an overview of simple binomial probabilities, classical scattering theory, quantum scattering and correlation, followed by the theory of single electron transition probabilities. Multiple electron transition probabilities are then treated in detail. Various approaches to multiple electron transitions are covered including the independent electron approximation, useful statistical methods and perturbation expansions treating correlation in both weak and strong limits. The important topic of the dynamics of electron correlation is a central theme in this book. The text contains a comprehensive summary of data for few and many-electron transitions in atoms and molecules, including transitions on different atomic centres, fast ion-atom and electron-atom interactions, and recent ob

Mechanisms are fundamental components of machines. They are used to transmit forces and moments and to manipulate objects in industrial machinery, robots, automobiles, aircraft, mechatronics devices and biomechanical systems. A knowledge of the kinematic and dynamic properties of mechanisms is essential for their design and control. This book describes methods and algorithms for the analysis of kinematic systems. Beginning with basic concepts, the book then discusses a variety of problem-solving approaches and computational techniques. Its distinctive feature is its focus on the contour equation as a powerful, computationally efficient tool that will help the reader to design complex spatial mechanisms. This handy text will be useful for senior or graduate students, researchers and practising engineers working in robotics, vehicle dynamics, mechatronics and machine design.

The interacting boson-fermion model has become in recent years the standard model for the description of atomic nuclei with an odd number of protons and/or neutrons. This book describes the mathematical framework on which the interacting boson-fermion model is built and presents applications to a variety of situations encountered in nuclei. The book addresses both the analytical and the numerical aspects of the problem. The analytical aspect requires the introduction of rather complex group theoretic methods, including the use of graded (or super) Lie algebras. The first (and so far only) example of supersymmetry occurring in nature is also discussed. The book is the first comprehensive treatment of the subject and will appeal to both theoretical and experimental physicists. The large number of explicit formulas for level energies, electromagnetic transition rates and intensities of transfer reactions presented in the book provide a simple but detailed way to analyse experimental data.

Do you have data that is not normally distributed and don't know how to analyze it using generalized linear models (GLM)? Beginning with a discussion of fundamental statistical modeling concepts in a

The second part of this two-volume set contains advanced aspects of the quantitative theory of the dynamics of neurons. It begins with an introduction to the effects of reversal potentials on response to synaptic input. It then develops the theory of action potential generation based on the seminal Hodgkin-Huxley equations and gives methods for their solution in the space-clamped and non-space-clamped cases. The remainder of the book discusses stochastic models of neural activity and ends with a statistical analysis of neuronal data with emphasis on spike trains. The mathematics is more complex in this volume than in the first volume and involves numerical methods of solution of partial differential equations and the statistical analysis of point processes.

Measuring Computer Performance sets out the fundamental techniques used in analyzing and understanding the performance of computer systems. Throughout the book, the emphasis is on practical methods of measurement, simulation, and analytical modeling. The author discusses performance metrics and provides detailed coverage of the strategies used in benchmark programmes. He gives intuitive explanations of the key statistical tools needed to interpret measured performance data. He also describes the general 'design of experiments' technique, and shows how the maximum amount of information can be obtained for the minimum effort. The book closes with a chapter on the technique of queueing analysis. Appendices listing common probability distributions and statistical tables are included, along with a glossary of important technical terms. This practically-oriented book will be of great interest to anyone who wants a detailed, yet intuitive, understanding of computer systems performance analysi

Tools developed by statistical physicists are of increasing importance in the analysis of complex biological systems. Physics in Molecular Biology, first published in 2005, discusses how physics can be used in modeling life. It begins by summarizing important biological concepts, emphasizing how they differ from the systems normally studied in physics. A variety of topics, ranging from the properties of single molecules to the dynamics of macro-evolution, are studied in terms of simple mathematical models. The main focus of the book is on genes and proteins and how they build systems that compute and respond. The discussion develops from simple to complex systems, and from small-scale to large-scale phenomena. This book will inspire advanced undergraduates and graduate students in physics to approach biological subjects from a physicist's point of view. It is self-contained, requiring no background knowledge of biology, and only familiarity with basic concepts from physics, such as for

This book shows how practitioners in the emerging field of 'cultural epidemiology' describe human health, communicate with diverse audiences, and intervene to improve health and prevent disease. It uses textual and statistical portraits of disease to describe past and present collaborations between anthropology and epidemiology. Interpreting epidemiology as a cultural practice helps to reveal the ways in which measurement, causal thinking, and intervention design are all influenced by belief, habit, and theories of power. By unpacking many common disease risks and epidemiologic categories, this book reveals unexamined assumptions and shows how sociocultural context influences measurement of disease. Examples include studies of epilepsy, cholera, mortality on the Titanic, breastfeeding, and adolescent smoking. The book describes methods as varied as observing individuals, measuring social networks, and compiling data from death certificates. It argues that effective public health interv

This book shows how practitioners in the emerging field of 'cultural epidemiology' describe human health, communicate with diverse audiences, and intervene to improve health and prevent disease. It uses textual and statistical portraits of disease to describe past and present collaborations between anthropology and epidemiology. Interpreting epidemiology as a cultural practice helps to reveal the ways in which measurement, causal thinking, and intervention design are all influenced by belief, habit, and theories of power. By unpacking many common disease risks and epidemiologic categories, this book reveals unexamined assumptions and shows how sociocultural context influences measurement of disease. Examples include studies of epilepsy, cholera, mortality on the Titanic, breastfeeding, and adolescent smoking. The book describes methods as varied as observing individuals, measuring social networks, and compiling data from death certificates. It argues that effective public health interv