Statistical Complexity

Who would have guessed that four minutes could change everything?Today should be one of the worst days of seventeen-year-old Hadley Sullivan's life. Having missed her flight, she's stuck at JFK airpor

本書是一部系統性探討海洋與沿岸波浪的專業著作，兼顧物理意義與統計分析，適合研究所學生、研究人員與工程實務者閱讀。內容從觀測技術談起，介紹現地量測與遙測方法，並逐步建立描述波浪的參數與統計架構。書中詳述線性波理論在外海與近岸水域的應用，說明波浪在不同水深與地形條件下的行為差異，並深入介紹 SWAN 波浪模式，協助讀者理解現代數值模擬在工程與研究中的角色。全書結構嚴謹、插圖清楚，是理解風生波浪與海岸波動不可或缺的參考書。Waves in Oceanic and Coastal Waters describes the observation, analysis and prediction of wind-generated waves in the open ocean, in shelf seas, and in coastal regions with islands, channels, tidal flats and inlets, estuaries, fjords and lagoons. Most of this richly illustrated book is devoted to the physical aspects of waves. After introducing observation techniques for waves, both at sea and from space, the book defines the parameters that characterise waves. Using basic statistical and physical concepts, the author discusses the prediction of waves in oceanic and coastal waters, first in terms of generalised observations, and then in terms of the more theoretical framework of the spectral energy balance. He gives the results of established theories and also the direction in wh

Why did the stock market crash more than 500 points on a single Monday in 1987? Why do ancient species often remain stable in the fossil record for millions of years and then suddenly disappear? In a

This book focuses on recent progress in complexity research based on the fundamental nonlinear dynamical and statistical theory of oscillations, waves, chaos, and structures far from equilibrium. Cele

In recent years, interest in developing statistical and computational techniques for applied manufacturing engineering has been increased. Today, due to the great complexity of manufacturing engineeri

Presents 20 statistical case studies for the classroom using data sets that have not been simplified for classroom use; that is, they retain the complexity of real-life statistical problems. The stud

Complexity theory aims to understand and classify computational problems, especially decision problems, according to their inherent complexity. This book uses new techniques to expand the theory for use with counting problems. The authors present dichotomy classifications for broad classes of counting problems in the realm of P and NP. Classifications are proved for partition functions of spin systems, graph homomorphisms, constraint satisfaction problems, and Holant problems. The book assumes minimal prior knowledge of computational complexity theory, developing proof techniques as needed and gradually increasing the generality and abstraction of the theory. This volume presents the theory on the Boolean domain, and includes a thorough presentation of holographic algorithms, culminating in classifications of computational problems studied in exactly solvable models from statistical mechanics.

Zero-knowledge interactive proofs play a central role in the design and study of cryptographic protocols and are rich objects for complexity-theoretic study. Statistical zero-knowledge (SZK) proofs ac

Complexity science is the study of systems with many interdependent components. Such systems - and the self-organization and emergent phenomena they manifest - lie at the heart of many challenges of global importance. This book is a coherent introduction to the mathematical methods used to understand complexity, with plenty of examples and real-world applications. It starts with the crucial concepts of self-organization and emergence, then tackles complexity in dynamical systems using differential equations and chaos theory. Several classes of models of interacting particle systems are studied with techniques from stochastic analysis, followed by a treatment of the statistical mechanics of complex systems. Further topics include numerical analysis of PDEs, and applications of stochastic methods in economics and finance. The book concludes with introductions to space-time phases and selfish routing. The exposition is suitable for researchers, practitioners and students in complexity sci

The complexity, diversity, and random nature of transportation problems necessitates a broad analytical toolbox. Describing tools commonly used in the field, Statistical and Econometric Methods for Tr

The structural mechanics of proteins that fold into functional shapes, polymers that aggregate and form clusters, and organic macromolecules that bind to inorganic matter can only be understood through statistical physics and thermodynamics. This book reviews the statistical mechanics concepts and tools necessary for the study of structure formation processes in macromolecular systems that are essentially influenced by finite-size and surface effects. Readers are introduced to molecular modeling approaches, advanced Monte Carlo simulation techniques, and systematic statistical analyses of numerical data. Applications to folding, aggregation, and substrate adsorption processes of polymers and proteins are discussed in great detail. Particular emphasis is placed on the reduction of complexity by coarse-grained modeling, which allows for the efficient, systematic investigation of structural phases and transitions. Providing insight into modern research at this interface between physics,

The complexity of social problems necessitates that social work researchers understand and apply multivariate statistical methods in their investigations. In this pocket guide, the authors introduce r

Integrates traditional statistical data analysis with new computational experimentation capabilities and concepts of algorithmic complexity and chaotic behavior in nonlinear dynamic systems, offering

These notes are based on a series of lectures given at the Advanced Research Institute of Discrete Applied Mathematics held at Rutgers University. Their aim is to link together algorithmic problems arising in knot theory, statistical physics and classical combinatorics. Apart from the theory of computational complexity concerned with enumeration problems, introductions are given to several of the topics treated, such as combinatorial knot theory, randomised approximation algorithms, percolation and random cluster models. To researchers in discrete mathematics, computer science and statistical physics, this book will be of great interest, but any non-expert should find it an appealing guide to a very active area of research.

Statistical mechanics is our tool for deriving the laws that emerge from complex systems. Sethna's text distills the subject to be accessible to those in all realms of science and engineering - avoidi

The book is a collection of papers of experts in the fields of information and complexity. Information is a basic structure of the world, while complexity is a fundamental property of systems and proc

Introduction to Statistical Investigations leads students to learn about the process of conducting statistical investigations from data collection, to exploring data, to statistical inference, to

Introduction to Statistical Investigations, 1st Edition leads readers to learn about the process of conducting statistical investigations from data collection, to exploring data, to statistical i

This book examines the question of whether languages can differ in grammatical complexity and, if so, how relative complexity differences might be measured. The volume differs from others devoted to t

Complexity of grammatical structure has become a center of interest in recent typological and dialectological research. The contributions of the present volume discuss structural complexity from the p

This textbook on statistical modeling and statistical inference will assist advanced undergraduate and graduate students. Statistical Modeling and Computation provides a unique introduction to modern

The application of statistical methods to physics is essential. This unique book on statistical physics offers an advanced approach with numerous applications to the modern problems students are confr

Because statistical confidentiality embraces the responsibility for both protecting data and ensuring its beneficial use for statistical purposes, those working with personal and proprietary data can

In this provocative and informative book, Don Norman writes that the complexity of our technology must mirror the complexity and richness of our lives. It’s not complexity that’s the problem; it’s bad

Models in Statistical Social Research provides a comprehensive insight of models used in statistical social research based on statistical data and methods. While traditionally understood statistical m

In response to the explosion in both the quantity and the complexity of data collections early in the 21st century, the Center for Statistical Research at the Chinese Academy of Science initiated the

Statistical techniques and theories have become widely applied in the physical, biological and social sciences. The enormous increase in their scope and complexity has led to much philosophical discussion of their significance, and of the meaning in non-mathematical terms of the methods and concepts they employ. This book deals not so much with statistical methods as with the central concept of chance, or statistical probability, which statistical theories apply to nature. Examples range from the chance of a tossed coin falling heads to that of a man dying or a radioactive atom decaying in a fixed period of time. Chances seem, however, to be peculiar properties, and to belong to peculiar entitles, to events rather than to things.

This textbook systematically presents fundamental methods of statistical analysis, from probability and statistical distributions, through basic concepts of statistical inference, to a collection of m

Global Complexity is a path-breaking book, which examines how the ideas of chaos and complexity can help us to analyse global processes. Urry argues that there are major advantages in thinking about g

Global Complexity is a path-breaking book, which examines how the ideas of chaos and complexity can help us to analyse global processes. Urry argues that there are major advantages in thinking about g

This book is intended for the statistician or student interested in becoming a statistical consultant and shows how to communicate statistical results effectively. It clearly illustrates what the con

Fast track route to mastering highly complex environments Covers the fundamentals of complexity, from encouraging iconoclastic behavior and setting up formal complexity training to using scenarios an

Statistical Parameters is a unique new guide to current statistical methods and research. Based on a series of interdisciplinary lectures for users of statistical methods in research and development,

Complex behaviour can occur in any system made up of large numbers of interacting constituents, be they atoms in a solid, cells in a living organism, or consumers in a national economy. Analysis of this behaviour often involves making important assumptions and approximations, the exact nature of which vary from subject to subject. Foundations of Complex-system Theories begins with a description of the general features of complexity and then examines a range of important concepts, such as theories of composite systems, collective phenomena, and stochastic processes. Each topic is discussed with reference to the fields of statistical physics, evolutionary biology, and economics, thereby highlighting recurrent themes in the study of complex systems. This detailed yet nontechnical book will appeal to anyone who wants to know more about complex systems and their behaviour. It will also be of great interest to specialists studying complexity in the physical, biological, and social sciences.

The twin themes of computational complexity and information pervade this 1998 book. It starts with an introduction to the computational complexity of continuous mathematical models, that is, information-based complexity. This is then used to illustrate a variety of topics, including breaking the curse of dimensionality, complexity of path integration, solvability of ill-posed problems, the value of information in computation, assigning values to mathematical hypotheses, and new, improved methods for mathematical finance. The style is informal, and the goals are exposition, insight and motivation. A comprehensive bibliography is provided, to which readers are referred for precise statements of results and their proofs. As the first introductory book on the subject it will be invaluable as a guide to the area for the many students and researchers whose disciplines, ranging from physics to finance, are influenced by the computational complexity of continuous problems.

The Likelihood plays a key role in both introducing general notions of statistical theory, and in developing specific methods. This book introduces likelihood-based statistical theory and related met

The first unified introduction and reference for the field of computational complexity. Virtually non-existent only 25 years ago, computational complexity has expanded tremendously and now comprises a

Communication Complexity describes a new intuitive model for studying circuit networks that captures the essence of circuit depth. Although the complexity of boolean functions has been studied for alm

This classic text combines thermodynamics, statistical mechanics, and kinetic theory in a single unified presentation of thermal physics. The three-part treatment covers the principles of statistical

In Complexity Economics for Environmental Governance, Jean-François Mercure reframes environmental policy and provides a rigorous methodology necessary to tackle the complexity of environmental policy and the transition to sustainability. The book offers a detailed account of the deficiencies of environmental economics and then develops a theory of innovation and macroeconomics based on complexity theory. It also develops a new foundation for evidence-based policy-making using a Risk-Opportunity Analysis applied to the sustainability transition. This multidisciplinary work was developed in partnership with prominent natural scientists and economists as well as active policy-makers with the aim to revolutionize thinking in the face of the full complexity of the sustainability transition, and to show how it can best be governed to minimize its distributional impacts. The book should be read by academics and policy-makers seeking new ways to think about environmental policy-making.