Functional Analysis Methods for Reliability Models

Tools to Safeguard New Buildings and Assess Existing OnesNonlinear analysis methods such as static pushover are globally considered a reliable tool for seismic and structural assessment. But the accur

Randomized algorithms have become a central part of the algorithms curriculum, based on their increasingly widespread use in modern applications. This book presents a coherent and unified treatment of probabilistic techniques for obtaining high probability estimates on the performance of randomized algorithms. It covers the basic toolkit from the Chernoff–Hoeffding bounds to more sophisticated techniques like martingales and isoperimetric inequalities, as well as some recent developments like Talagrand's inequality, transportation cost inequalities and log-Sobolev inequalities. Along the way, variations on the basic theme are examined, such as Chernoff–Hoeffding bounds in dependent settings. The authors emphasise comparative study of the different methods, highlighting respective strengths and weaknesses in concrete example applications. The exposition is tailored to discrete settings sufficient for the analysis of algorithms, avoiding unnecessary measure-theoretic details, thus making

This book represents an important part of the extension and expansion of the Functional Requirements for Bibliographic Records. It contains an analysis of attributes of various entities that are the c

Decomposition Methods for Differential Equations: Theory and Applications describes the analysis of numerical methods for evolution equations based on temporal and spatial decomposition methods. It co

This engaging textbook bridges the gap between traditional and functional grammar. Starting with a traditional approach, students will develop a firm grasp of traditional tools for analysis and learn

This engaging textbook bridges the gap between traditional and functional grammar. Starting with a traditional approach, students will develop a firm grasp of traditional tools for analysis and learn

Reveals How HMMs Can Be Used as General-Purpose Time Series ModelsImplements all methods in RHidden Markov Models for Time Series: An Introduction Using R applies hidden Markov models (HMMs) to a wide

This handbook studies the combination of various methods of designing for reliability, availability, maintainability and safety, as well as the latest techniques in probability and possibility modeli

The rapid development of the theories of Volterra integral and functional equations has been strongly promoted by their applications in physics, engineering and biology. This text shows that the theory of Volterra equations exhibits a rich variety of features not present in the theory of ordinary differential equations. The book is divided into three parts. The first considers linear theory and the second deals with quasilinear equations and existence problems for nonlinear equations, giving some general asymptotic results. Part III is devoted to frequency domain methods in the study of nonlinear equations. The entire text analyses n-dimensional rather than scalar equations, giving greater generality and wider applicability and facilitating generalizations to infinite-dimensional spaces. The book is generally self-contained and assumes only a basic knowledge of analysis. The many exercises illustrate the development of the theory and its applications, making this book accessible to res

'This book bridges disciplines, previously confined to specialist journal publications, by providing a comprehensive overview of the systems analysis application to water resources. It is ideal for Ma

The book provides a simple, intuitive introduction to regression models for qualitative and discrete dependent variables, to sample selection models, and to event history models, all in the context of

The combination of faster, more advanced computers and more quantitatively oriented biomedical researchers has recently yielded new and more precise methods for the analysis of biomedical data. These

This book provides a survey of the frontiers of research in the numerical modeling and mathematical analysis used in the study of the atmosphere and oceans. The details of the current practices in glo

A Decade of Extraordinary GrowthThe past decade has brought a surge of growth in the technologies for digital color imaging, multidimensional signal processing, and visual scene analysis. These advanc

Presents a wide variety of mass spectrometry methods used to explore structural mechanisms, protein dynamics and interactions between proteins. Preliminary chapters cover mass spectrometry methods fo

Although many books currently available describe statistical models and methods for analyzing longitudinal data, they do not highlight connections between various research threads in the statistical l

Although the Trefftz finite element method (FEM) has become a powerful computational tool in the analysis of plane elasticity, thin and thick plate bending, Poisson’s equation, heat conduction, and pi

Ecological Models and Data in R is the first truly practical introduction to modern statistical methods for ecology. In step-by-step detail, the book teaches ecology graduate students and researchers

Designed as a guide for new evaluators as well as for students, this provides insights on data gathering, analysis, and efficient operating procedures. Daponte (research, Institution for Social and Po

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

Numerical Methods in Finance has emerged as a discipline at the intersection of probability theory, finance and numerical analysis. This book, based on lectures given at the Newton Institute as part of a broader programme, describes a wide variety of numerical methods used in financial analysis: computation of option prices, especially of American option prices, by finite difference and other methods; numerical solution of portfolio management strategies; statistical procedures; identification of models; Monte Carlo methods; and numerical implications of stochastic volatilities. Articles have been written in a pedagogic style and made reasonably self-contained, covering both mathematical matters and practical issues in numerical problems. Thus the book has something to offer economists, probabilists and applied mathematicians working in finance.

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

Infectious disease accounts for more death and disability globally than either non-infectious disease or injury. This book contains a breadth of different quantitative approaches to understanding the patterns of infectious diseases in populations, and the design of control strategies to lessen their effect. The contributors bring a great variety of mathematical expertise (including deterministic and stochastic modelling and statistical data analysis) and involvement in a wide range of applied fields across the spectrum of biological, medical and social sciences. The aim is to increase interaction between specialities by describing research on many of the infectious diseases that affect humans, including both viral diseases like measles and AIDS and tropical parasitic infections. The papers are divided into groups dealing with problems relating to transmissible diseases, vaccination strategies, the consequences of treatment interventions, the dynamics of immunity, heterogeneity of popu

Employing a uniform, easy-to-use format, Vitamin Analysis for the Health and Food Sciences, Second Edition provides the most current information on the methods of vitamin analysis applicable to foods,

The study of fire debris analysis is vital to the function of all fire investigations, and, as such, Fire Debris Analysis is an essential resource for fire investigators. The present methods of analys

This book describes the philosophy of functional-structural plant modelling and several tools for making FSPMs; it outlines methods for measuring essential parameters, including those pertaining to pl

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

The first all-inclusive introduction to modern statistical research methods in the natural resource sciences The use of Bayesian statistical analysis has become increasingly important to natural reso

What you’ll find in this monograph is nothing less than a complete and rigorous study of modern functional analysis. It is intended for the student or researcher who could benefit from functional anal

This book describes the philosophy of functional-structural plant modelling and several tools for making FSPMs; it outlines methods for measuring essential parameters, including those pertaining to pl

Bayesian Networks are a form of probabilistic graphical models and they are used for modeling knowledge in many application areas, from medicine to image processing. They are particularly useful for b

This timely overview of the syntheses for functional pi-systems focuses on target molecules that have shown interesting properties as materials or models in physics, biology and chemistry. The unique

A group of international academics provides a broad overview of the use of reference models in the analysis of business systems. Several of the 16 peer-reviewed contributions discuss the process of de

What you’ll find in this monograph is nothing less than a complete and rigorous study of modern functional analysis. It is intended for the student or researcher who could benefit from functional anal

Electronic structure problems are studied in condensed matter physics and theoretical chemistry to provide important insights into the properties of matter. This 2006 graduate textbook describes the main theoretical approaches and computational techniques, from the simplest approximations to the most sophisticated methods. It starts with a detailed description of the various theoretical approaches to calculating the electronic structure of solids and molecules, including density-functional theory and chemical methods based on Hartree-Fock theory. The basic approximations are thoroughly discussed, and an in-depth overview of recent advances and alternative approaches in DFT is given. The second part discusses the different practical methods used to solve the electronic structure problem computationally, for both DFT and Hartree-Fock approaches. Adopting a unique and open approach, this textbook is aimed at graduate students in physics and chemistry, and is intended to improve communicat

Longitudinal data analysis for biomedical and behavioral sciences This innovative book sets forth and describes methods for the analysis of longitudinaldata, emphasizing applications to problems in t

John Barnes's collection of essays covers a variety of topics in sociology and anthropology, including lineage systems, social networks, colonialism, underlying assumptions of social science, and the significance of time in social analysis. Together they identify the author's particular view of social science: he is primarily interested in 'what really happens'. Rather than revamp articles written with a distinctive set of assumptions to bring them into line with current intellectual fashion, Professor Barnes has chosen to let them stand as they are, products of identifiable theoretical stance and modes of exposition. But introductory notes to each chapter set out the context in which the piece was originally written and draw attention to later publications and events that bear on it. An introduction discusses in detail the author's view of social science as the construction of models rather than a search for social laws, while the final chapter presents a model of the modelling proces

A timely, hands-on guide to environmental issues and regulatory standards for the petroleum industry Environmental analysis and testing methods are an integral part of any current and future refining