Functional Analysis Methods for Reliability Models

This text provides a basis for the analysis of optimization models and candidate optimal solutions, especially for continuous optimization models. The treatment focuses on the analysis and algebra tha

Analytical Solution Methods for Boundary Value Problems is an extensively revised, new English language edition of the original 2011 Russian language work, which provides deep analysis methods and exa

This book focuses on statistical methods for the analysis of discrete failure times. Failure time analysis is one of the most important fields in statistical research, with applications affecting a wi

This book describes the methods and numerical approaches for data assimilation in geodynamical models and presents several applications of the described methodology in relevant case studies. The book

Forecasting Urban Travel presents in a non-mathematical way the evolution of methods, models and theories underpinning travel forecasts and policy analysis, from the early urban transportation studies

Many problems in biology require an understanding of the relationships among variables in a multivariate causal context. Exploring such cause-effect relationships through a series of statistical methods, this book explains how to test causal hypotheses when randomised experiments cannot be performed. This completely revised and updated edition features detailed explanations for carrying out statistical methods using the popular and freely available R statistical language. Sections on d-sep tests, latent constructs that are common in biology, missing values, phylogenetic constraints, and multilevel models are also an important feature of this new edition. Written for biologists and using a minimum of statistical jargon, the concept of testing multivariate causal hypotheses using structural equations and path analysis is demystified. Assuming only a basic understanding of statistical analysis, this new edition is a valuable resource for both students and practising biologists.

The subject of this book is CMOS RF circuit design for reliability. The device reliability and process variation issues on RF transmitter and receiver circuits will be particular interest to the reade

The monograph presents a comparative analysis of different thermodynamic models of the equations of state. The basic ideological premises of the theoretical methods and the experiment are considered.

Featuring detailed explanations of the major algorithms used in quantum Monte Carlo simulations, this is the first textbook of its kind to provide a pedagogical overview of the field and its applications. The book provides a comprehensive introduction to the Monte Carlo method, its use, and its foundations, and examines algorithms for the simulation of quantum many-body lattice problems at finite and zero temperature. These algorithms include continuous-time loop and cluster algorithms for quantum spins, determinant methods for simulating fermions, power methods for computing ground and excited states, and the variational Monte Carlo method. Also discussed are continuous-time algorithms for quantum impurity models and their use within dynamical mean-field theory, along with algorithms for analytically continuing imaginary-time quantum Monte Carlo data. The parallelization of Monte Carlo simulations is also addressed. This is an essential resource for graduate students, teachers, and re

Focusing on up-to-date artificial intelligence models to solve building energy problems,Artificial Intelligence for Building Energy Analysis reviews recently developed models for solving these issues,

This is an exercises book at the beginning graduate level, whose aim is to illustrate some of the connections between functional analysis and the theory of functions of one variable. A key role is pla

This book deals with fractals in understanding problems encountered in earth science, and their solutions. It starts with an analysis of two classes of methods (homogeneous fractals random models, and

The widespread use of mouse models in developmental, behavioural and genetic studies has sparked wider interest in rodent biology as a whole. This book brings together the latest research on rodents to better understand the evolution of both living and extinct members of this fascinating group. Topics analysed include the role of molecular techniques in the determination of robust phylogenetic frameworks; how geometric morphometric methods help quantify and analyse variation in shape; and the role of developmental biology in elucidating the origins of skeletal elements and the teeth. The editors unite these disciplines to present the current state of knowledge in rodent biology, whilst setting the landscape for future research. This book highlights interdisciplinary links across palaeontology, developmental biology, functional morphology, phylogenetics and biomechanics, making it a valuable resource for evolutionary biologists in all fields.

This brief presents emerging and promising communication methods for network reliability via delay tolerant networks (DTNs). Different from traditional networks, DTNs possess unique features, such as

Based on a starter course for beginning graduate students, Core Statistics provides concise coverage of the fundamentals of inference for parametric statistical models, including both theory and practical numerical computation. The book considers both frequentist maximum likelihood and Bayesian stochastic simulation while focusing on general methods applicable to a wide range of models and emphasizing the common questions addressed by the two approaches. This compact package serves as a lively introduction to the theory and tools that a beginning graduate student needs in order to make the transition to serious statistical analysis: inference; modeling; computation, including some numerics; and the R language. Aimed also at any quantitative scientist who uses statistical methods, this book will deepen readers' understanding of why and when methods work and explain how to develop suitable methods for non-standard situations, such as in ecology, big data and genomics.

Based on a starter course for beginning graduate students, Core Statistics provides concise coverage of the fundamentals of inference for parametric statistical models, including both theory and practical numerical computation. The book considers both frequentist maximum likelihood and Bayesian stochastic simulation while focusing on general methods applicable to a wide range of models and emphasizing the common questions addressed by the two approaches. This compact package serves as a lively introduction to the theory and tools that a beginning graduate student needs in order to make the transition to serious statistical analysis: inference; modeling; computation, including some numerics; and the R language. Aimed also at any quantitative scientist who uses statistical methods, this book will deepen readers' understanding of why and when methods work and explain how to develop suitable methods for non-standard situations, such as in ecology, big data and genomics.

Praise for the First Edition"…[t]he book is great for readers who need to apply the methods and models presented but have little background in mathematics and statistics." -MAA Revie

Describes and discusses the variants of kernel analysis methods for data types that have been intensely studied in recent yearsThis book covers kernel analysis topics ranging from the fundamental theo

This book provides an introduction to investment appraisal and presents a range of methods and models, some of which are not widely known, or at least not well covered by other textbooks. Each approac

This book provides an introduction into data mining methods and models, including association rules, clustering, neural networks, logistic regression, and multivariate analysis. In addition, this revi

This comprehensive content and reference work on atmospheric models covers not only the methods for numerical modeling, but also the related fields of assimilation and predictability. It includes dist

This book gives introductory chapters on the classical basic and standard methods for asymptotic analysis, such as Watson's lemma, Laplace's method, the saddle point and steepest descent methods, stat

This book covers the recent advancement of statistical methods for the analysis of longitudinal data. Real datasets from four large NIH-supported longitudinal clinical trials and epidemiological studi

This volume provides an overview of modern and emerging methods for production, analysis, and utility of peptide libraries. Chapter focus on methods and techniques for synthesis, genetic expression, h

Economic Analysis of Industrial Projects, Third Edition, provides the best possible methods for applying economic analysis theory to practice. Completely revised and expanded in this new edition, the

Nursing Research Using Data Analysis: Qualitative Designs and Methods in Nursing is one book in a series of seven volumes that presents concise, how-to guides to conducting qualitative research -- for

"The book provides information on the methods of analysis and related modeling techniques suitable for the design and evaluation of various types of bridges. For the purpose of analysis, several speci

Diffusion wavelets are powerful tools for functional analysis and geometry processing, enabling researchers to determine the structure of data and analyze 3D shapes. This is the first book on diffusio

This book opens new avenues in understanding mathematical models within the context of a transition economy. The exposition lays out the methods for combining different mathematical structures and too

As in the previous Seminar Notes, the current volume reflects general trends in the study of Geometric Aspects of Functional Analysis. Most of the papers deal with different aspects of Asymptotic Geom

In this book the authors introduce and explain many methods and models for the development of Information Systems (IS). It was written in large part to aid designers in designing successful devices/sy

This book describes a system of mathematical models and methods that can be used to analyze real economic and managerial decisions and to improve their effectiveness. Application areas include: manage

This book provides a comprehensive, coherent, and intuitive review of panel data methodologies that are useful for empirical analysis. Substantially revised from the second edition, it includes two new chapters on modeling cross-sectionally dependent data and dynamic systems of equations. Some of the more complicated concepts have been further streamlined. Other new material includes correlated random coefficient models, pseudo-panels, duration and count data models, quantile analysis, and alternative approaches for controlling the impact of unobserved heterogeneity in nonlinear panel data models.

This book provides a comprehensive, coherent, and intuitive review of panel data methodologies that are useful for empirical analysis. Substantially revised from the second edition, it includes two new chapters on modeling cross-sectionally dependent data and dynamic systems of equations. Some of the more complicated concepts have been further streamlined. Other new material includes correlated random coefficient models, pseudo-panels, duration and count data models, quantile analysis, and alternative approaches for controlling the impact of unobserved heterogeneity in nonlinear panel data models.

The second volume of this systematical presentation of stochastic approximation methods for models of American-type options presents results on structural studies of optimal stopping domains, Monte Ca

Introducing time series methods and their application in social science research, this practical guide to time series models is the first in the field written for a non-econometrics audience. Giving r

Quantitative Intelligence Analysis describes a model-based method of intelligence analysis that explicitly represents the analyst’s mental models of a subject, as well as the analyst’s reasoning proce

Metabolic Flux Analysis: Methods and Protocols opens up the field of metabolic flux analysis to those who want to start a new flux analysis project but are overwhelmed by the complexity of the approac

Analysis, modeling, and simulation for better understanding of diverse complex natural and social phenomena often require powerful tools and analytical methods. Tractable approaches, however, can be d

This textbook is an introduction to functional analysis suited to final year undergraduates or beginning graduates. Its various applications of Hilbert spaces, including least squares approximation, i