Functional Analysis Methods for Reliability Models

Experts describe advanced techniques for the chemical synthesis of functional organic nanoparticles and propose new methods for the characterization and manipulation of single nanoparticles. Theoretic

Emphasizing a quantitative approach, Supply Chain Engineering: Models and Applications provides state-of-the-art mathematical models, concepts, and solution methods important in the design, control, o

Materials and Reliability Handbook for Semiconductor Optical and Electron Devices provides comprehensive coverage of reliability procedures and approaches for electron and photonic devices. These incl

Generalized Linear Mixed Models: Modern Concepts, Methods and Applications presents an introduction to linear modeling using the generalized linear mixed model (GLMM) as an overarching conceptual fram

The techniques that can be used to solve non-linear problems are far different than those that are used to solve linear problems. Many courses in analysis and applied mathematics attack linear cases simply because they are easier to solve and do not require a large theoretical background in order to approach them. Professor Schechter's 2005 book is devoted to non-linear methods using the least background material possible and the simplest linear techniques. An understanding of the tools for solving non-linear problems is developed whilst demonstrating their application to problems in one dimension and then leading to higher dimensions. The reader is guided using simple exposition and proof, assuming a minimal set of pre-requisites. For completion, a set of appendices covering essential basics in functional analysis and metric spaces is included, making this ideal as an accompanying text on an upper-undergraduate or graduate course, or even for self-study.

Asymptotic analysis of stochastic stock price models is the central topic of the present volume. Special examples of such models are stochastic volatility models, that have been developed as an answer

Analysis and Interpretation of Ethnographic Data: A Mixed Methods Approach,Second Edition, is a comprehensive treatment of analysis strategies used inethnographic research, addressing the “crunching”

This new edition updates Durbin & Koopman's important text on the state space approach to time series analysis. The distinguishing feature of state space time series models is that observations are re

"The aim of Design for Reliability (DFR) is to design for zero failures of critical system functions, which results in enormous savings in life cycle costs for producers and users. This practical guid

"Preface Joint models for longitudinal and time-to-event data have become a valuable tool in the analysis of follow-up data. These models are applicable mainly in two settings: First, when focus is in

"Risk analysis is crucial in stochastic supply chain models. Over the past few years, the pace has quickened for research attempting to explore risk analysis issues in supply chain management problem

This book introduces advanced numerical-functional analysis to beginning computer science researchers. The reader is assumed to have had basic courses in numerical analysis, computer programming, comp

Image Analysis in Earth Sciences is a graduate level textbook for researchers and students interested in the quantitative microstructure and texture analysis of earth materials. Methods of analysis an

How can I supercharge the therapy I currently use?This volume distils the core principles, methods, and vision of the approach. Each Functional Analytic Psychotherapy (FAP) principle is presented in t

How can I supercharge the therapy I currently use?This volume distils the core principles, methods, and vision of the approach. Each Functional Analytic Psychotherapy (FAP) principle is presented in t

The book focuses on the use of inelastic analysis methods for the seismic assessment and design of bridges, for which the work carried out so far, albeit interesting and useful, is nevertheless clearl

How does the practice of archaeology benefit from faunal analysis? Michael Glassow and Terry Joslin's Exploring Methods of Faunal Analysis: Insights from California Archaeology addresses this question

Numerical Methods provides a clear and concise exploration of standard numerical analysis topics, as well as nontraditional ones, including mathematical modeling, Monte Carlo methods, Markov chains, a

The theme of the meeting was “Statistical Methods for the Analysis of Large Data-Sets”. In recent years there has been increasing interest in this subject; in fact a huge quantity of information is of

Compact Models and Measurement Techniques for High-Speed Interconnects provides detailed analysis of issues related to high-speed interconnects from the perspective of modeling approaches and measurem

Presenting a complementary perspective to standard books on algorithms, A Guide to Algorithm Design: Paradigms, Methods, and Complexity Analysis provides a roadmap for readers to determine the difficu

This text/reference is a detailed look at the development and use of integral equation methods for electromagnetic analysis, specifically for antennas and radar scattering. Developers and practitioner

A book in the Systems Evaluation, Prediction, and Decision-Making Series, Systems Evaluation: Methods, Models, and Applications covers the evolutionary course of systems evaluation methods, clearly an

Revised and?updated, this second edition of Walter Gautschi's successful Numerical Analysis?explores?computational methods?for problems arising in the areas of classical analysis, approximation theory

The most recent methods and strategies for the elucidation of protein and peptide structures, e.g. sensitive techniques for the analysis of primary structure and amino acid sequences as well as second

Written to provide business architecture models, methods, and an application for developing business architecture that connects the business to information technology, this book provides a methodology

This book introduces basic and advanced concepts of categorical regression with a focus on the structuring constituents of regression, including regularization techniques to structure predictors. In addition to standard methods such as the logit and probit model and extensions to multivariate settings, the author presents more recent developments in flexible and high-dimensional regression, which allow weakening of assumptions on the structuring of the predictor and yield fits that are closer to the data. A generalized linear model is used as a unifying framework whenever possible in particular parametric models that are treated within this framework. Many topics not normally included in books on categorical data analysis are treated here, such as nonparametric regression; selection of predictors by regularized estimation procedures; ternative models like the hurdle model and zero-inflated regression models for count data; and non-standard tree-based ensemble methods. The book is accom

This book covers competing risks and multistate models, sometimes summarized as event history analysis. These models generalize the analysis of time to a single event (survival analysis) to analysing

?Mechanics, Models and Methods in Civil Engineering” collects leading papers dealing with actual Civil Engineering problems. The approach is in the line of the Italian-French school and therefore deep

The book addresses software design issues related to methods for the analysis of construction engineering by means of modern CAD (computer-aided design) systems and provides validation for their use.

'What's going to happen next?' Time series data hold the answers, and Bayesian methods represent the cutting edge in learning what they have to say. This ambitious book is the first unified treatment of the emerging knowledge-base in Bayesian time series techniques. Exploiting the unifying framework of probabilistic graphical models, the book covers approximation schemes, both Monte Carlo and deterministic, and introduces switching, multi-object, non-parametric and agent-based models in a variety of application environments. It demonstrates that the basic framework supports the rapid creation of models tailored to specific applications and gives insight into the computational complexity of their implementation. The authors span traditional disciplines such as statistics and engineering and the more recently established areas of machine learning and pattern recognition. Readers with a basic understanding of applied probability, but no experience with time series analysis, are guided fro

The success of the Apgar score demonstrates the astounding power of an appropriate clinical instrument. This down-to-earth book provides practical advice, underpinned by theoretical principles, on developing and evaluating measurement instruments in all fields of medicine. It equips you to choose the most appropriate instrument for specific purposes. The book covers measurement theories, methods and criteria for evaluating and selecting instruments. It provides methods to assess measurement properties, such as reliability, validity and responsiveness, and interpret the results. Worked examples and end-of-chapter assignments use real data and well-known instruments to build your skills at implementation and interpretation through hands-on analysis of real-life cases. All data and solutions are available online. This is a perfect course book for students and a perfect companion for professionals/researchers in the medical and health sciences who care about the quality and meaning of the

The success of the Apgar score demonstrates the astounding power of an appropriate clinical instrument. This down-to-earth book provides practical advice, underpinned by theoretical principles, on developing and evaluating measurement instruments in all fields of medicine. It equips you to choose the most appropriate instrument for specific purposes. The book covers measurement theories, methods and criteria for evaluating and selecting instruments. It provides methods to assess measurement properties, such as reliability, validity and responsiveness, and interpret the results. Worked examples and end-of-chapter assignments use real data and well-known instruments to build your skills at implementation and interpretation through hands-on analysis of real-life cases. All data and solutions are available online. This is a perfect course book for students and a perfect companion for professionals/researchers in the medical and health sciences who care about the quality and meaning of the

This proceedings is a collection of articles by front-line researchers in Mathematical Analysis, giving the reader a wide perspective of the current research in several areas like Functional Analysis,

Analysis of Structures offers a new way of introducing engineering students to the subject of stress and deformation analysis of solid objects and to become more familiar with how numerical methods su

Artificial intelligence and expert systems have seen a great deal of research in recent years, much of which has been devoted to methods for incorporating uncertainty into models. This book is devoted

Portfolio Decision Analysis: Improved Methods for Resource Allocation provides an extensive, up-to-date coverage of decision analytic methods which help firms and public organizations allocate resourc

Reliability and Safety of Complex Technical Systems and Processes offers a comprehensive approach to the analysis, identification, evaluation, prediction and optimization of complex technical systems

This book describes methods and software implementations for the analysis of interval-censored data. The authors present the theoretical background for all methods and apply the methods to real data s

The choices made in selecting participants for a research study are critical to the validity and reliability of the findings of the study, says Daniel (research methods and statistics, Howard U.), no