Functional Analysis Methods for Reliability Models

Survival analysis is a class of statistical methods for studying the occurrence and timing of events. Statistical analysis of longitudinal data, particularly censored data, lies at the heart of social

In recent years cosmologists have advanced from largely qualitative models of the Universe to precision modelling using Bayesian methods, in order to determine the properties of the Universe to high accuracy. This timely book is the only comprehensive introduction to the use of Bayesian methods in cosmological studies, and is an essential reference for graduate students and researchers in cosmology, astrophysics and applied statistics. The first part of the book focuses on methodology, setting the basic foundations and giving a detailed description of techniques. It covers topics including the estimation of parameters, Bayesian model comparison, and separation of signals. The second part explores a diverse range of applications, from the detection of astronomical sources (including through gravitational waves), to cosmic microwave background analysis and the quantification and classification of galaxy properties. Contributions from 24 highly regarded cosmologists and statisticians make

This 2000 publication reviews the rapid development of functional neuroimaging techniques and their implications for child psychiatry. It is unusual in its focus on children, and in integrating brain mapping with genetics and behavioural testing. This reference will help clinicians and investigators to: • Understand through imaging the mechanisms of childhood psychiatric disorders • Decide which technique is most appropriate for their purposes, with respect to technology, experimental design, data analysis and ethical considerations • Appreciate the role of molecular genetics and neuropsychology in planning brain imaging studies Coverage includes description of brain imaging strategies and the application to children of imaging techniques used in adults, set against an overview of normal behavioural and cognitive development. Linking the latest findings from neuroimaging to neurophysiological models, this is an essential resource for researchers and clinicians concerned with neurodevel

This work gathers recent international research on vision-based systems for analyzing and interpreting motion from video footage. Chapter topics include graphical models for representation and recogni

Essentials of Applied Quantitative Methods for Health Services offers and stresses the application of concepts, models and techniques in understanding quantitative methods in the health service field.

To address the increasing demands of device scaling, new materials are being introduced into conventional Si CMOS processing at an unprecedented rate. Presentations collected here focus on understanding, from a chemistry and materials perspective, the mechanism of interface formation and defects at interfaces, for both conventional Si and alternative channel (Ge or III-V) systems. Several papers address reliability concerns for high-k/metal gate (basic physical models, charge trapping, etc.), while others cover characterization of the thin films and interfaces which comprise the gate stack. Topics include: advanced Si-based gate stacks; and alternate channel materials.

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

Principles and Practices of Polymer Mass Spectrometry helps readers acquire the skills necessary for selecting the optimal methods, handling samples, analyzing the data, and interpreting the results o

Computational simulation of scientific phenomena and engineering problems often depends on solving linear systems with a large number of unknowns. This book gives insight into the construction of iterative methods for the solution of such systems and helps the reader to select the best solver for a given class of problems. The emphasis is on the main ideas and how they have led to efficient solvers such as CG, GMRES, and BI-CGSTAB. The author also explains the main concepts behind the construction of preconditioners. The reader is encouraged to gain experience by analysing numerous examples that illustrate how best to exploit the methods. The book also hints at many open problems and as such it will appeal to established researchers. There are many exercises that motivate the material and help students to understand the essential steps in the analysis and construction of algorithms.

This book represents a distinctive approach to cultural analysis, using multi-dimensional methods for addressing issues of public interest. The approach, which deploys Jim McGuigan's original concept

This book represents a distinctive approach to cultural analysis, using multi-dimensional methods for addressing issues of public interest. The approach, which deploys Jim McGuigan's original concept

Bio-Inspired Hybrid Intelligent Systems for Image Analysis and Pattern Recognition comprises papers on diverse aspects of bio-inspired models, soft computing and hybrid intelligent systems.The article

Bayesian methods are increasingly being used in the social sciences, as the problems encountered lend themselves so naturally to the subjective qualities of Bayesian methodology. This book provides a

Research during the past two decades has produced major advances in understanding sleep within particular species. Simultaneously, molecular advances have made it possible to generate phylogenetic trees, while new analytical methods provide the tools to examine macroevolutionary change on these trees. These methods have recently been applied to questions concerning the evolution of distinctive sleep state characteristics and functions. This book synthesizes recent advances in our understanding of the evolutionary origins of sleep and its adaptive function, and it lays the groundwork for future evolutionary research by assessing sleep patterns in the major animal lineages.

Functional Magnetic Resonance Imaging (fMRI) has become a standard tool for mapping the working brain's activation patterns, both in health and in disease. It is an interdisciplinary field and crosses the borders of neuroscience, psychology, psychiatry, radiology, mathematics, physics and engineering. Developments in techniques, procedures and our understanding of this field are expanding rapidly. In this second edition of Introduction to Functional Magnetic Resonance Imaging, Richard Buxton – a leading authority on fMRI – provides an invaluable guide to how fMRI works, from introducing the basic ideas and principles to the underlying physics and physiology. He covers the relationship between fMRI and other imaging techniques and includes a guide to the statistical analysis of fMRI data. This book will be useful both to the experienced radiographer, and the clinician or researcher with no previous knowledge of the technology.

Multivariable Modeling and Multivariate Analysis for the Behavioral Sciences shows students how to apply statistical methods to behavioral science data in a sensible manner. Assuming some familiarity

In these two lectures, first published in 1994, Peter Diamond explores how time is modelled in theoretical analyses of individual industries and of an entire economy. In the first lecture he considers equilibrium in a single market by examining the distinction between the short run and the long run in Marshallian analysis. He proposes an explicit modelling of time in place of Marshall's use of different atemporal models for different time frames. In the second lecture he turns to models of an entire economy, and begins by considering how and why models of an entire economy should differ from models of a single industry. Both cyclical and seasonal data on the behaviour of macro-economies are examined.

Written by one of the preeminent researchers in the field, this book provides a comprehensive exposition of modern analysis of causation. It shows how causality has grown from a nebulous concept into a mathematical theory with significant applications in the fields of statistics, artificial intelligence, economics, philosophy, cognitive science, and the health and social sciences. Judea Pearl presents and unifies the probabilistic, manipulative, counterfactual, and structural approaches to causation and devises simple mathematical tools for studying the relationships between causal connections and statistical associations. Cited in more than 2,100 scientific publications, it continues to liberate scientists from the traditional molds of statistical thinking. In this revised edition, Judea Pearl elucidates thorny issues, answers readers' questions, and offers a panoramic view of recent advances in this field of research. Causality will be of interest to students and professionals in a w

Risk and Reliability: Coastal and Hydraulic Engineering sets out the methods which are increasingly being required by Government Agencies for river and sea defence design and flood defence system mana

The second edition of Statistics and Data Analysis for Nursing , uses a conversational style to teach students how to use statistical methods and procedures to analyze research findings. Readers ar

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