Functional Analysis Methods for Reliability Models

Intended for researchers and practitioners in interaction design, this book shows how Bayesian models can be brought to bear on problems of interface design and user modelling. It introduces and motivates Bayesian modelling and illustrates how powerful these ideas can be in thinking about human-computer interaction, especially in representing and manipulating uncertainty. Bayesian methods are increasingly practical as computational tools to implement them become more widely available, and offer a principled foundation to reason about interaction design. The book opens with a self-contained tutorial on Bayesian concepts and their practical implementation, tailored for the background and needs of interaction designers. The contributed chapters cover the use of Bayesian probabilistic modelling in a diverse set of applications, including improving pointing-based interfaces; efficient text entry using modern language models; advanced interface design using cutting-edge techniques in Bayesia

A comprehensive introduction to the most commonly used statistical methods relevant in atmospheric, oceanic and climate sciences. Each method is described step-by-step using plain language, and illustrated with concrete examples, with relevant statistical and scientific concepts explained as needed. Particular attention is paid to nuances and pitfalls, with sufficient detail to enable the reader to write relevant code. Topics covered include hypothesis testing, time series analysis, linear regression, data assimilation, extreme value analysis, Principal Component Analysis, Canonical Correlation Analysis, Predictable Component Analysis, and Covariance Discriminant Analysis. The specific statistical challenges that arise in climate applications are also discussed, including model selection problems associated with Canonical Correlation Analysis, Predictable Component Analysis, and Covariance Discriminant Analysis. Requiring no previous background in statistics, this is a highly accessibl

In pioneering work in the 1950s, S. Karlin and J. McGregor showed that probabilistic aspects of certain Markov processes can be studied by analyzing orthogonal eigenfunctions of associated operators. In the decades since, many authors have extended and deepened this surprising connection between orthogonal polynomials and stochastic processes. This book gives a comprehensive analysis of the spectral representation of the most important one-dimensional Markov processes, namely discrete-time birth-death chains, birth-death processes and diffusion processes. It brings together the main results from the extensive literature on the topic with detailed examples and applications. Also featuring an introduction to the basic theory of orthogonal polynomials and a selection of exercises at the end of each chapter, it is suitable for graduate students with a solid background in stochastic processes as well as researchers in orthogonal polynomials and special functions who want to learn about appl

This study guide is designed for students taking courses in electric power system analysis. The textbook includes examples, questions, and exercises that will help electric power engineering students to review and sharpen their knowledge of the subject and enhance their performance in the classroom. Offering detailed solutions, multiple methods for solving problems, and clear explanations of concepts, this hands-on guide will improve student's problem-solving skills and basic and advanced understanding of the topics covered in power system analysis courses.

Optimization techniques are at the core of data science, including data analysis and machine learning. An understanding of basic optimization techniques and their fundamental properties provides important grounding for students, researchers, and practitioners in these areas. This text covers the fundamentals of optimization algorithms in a compact, self-contained way, focusing on the techniques most relevant to data science. An introductory chapter demonstrates that many standard problems in data science can be formulated as optimization problems. Next, many fundamental methods in optimization are described and analyzed, including: gradient and accelerated gradient methods for unconstrained optimization of smooth (especially convex) functions; the stochastic gradient method, a workhorse algorithm in machine learning; the coordinate descent approach; several key algorithms for constrained optimization problems; algorithms for minimizing nonsmooth functions arising in data science; found

The field of forensic DNA analysis has grown immensely in the past two decades and genotyping of biological samples is now routinely performed in human identification (HID) laboratories. Application areas include paternity testing, forensic casework, family lineage studies, identification of human remains, and DNA databasing. Forensic DNA Analysis: Current Practices and Emerging Technologies explores the fundamental principles and the application of technologies for each aspect of forensic DNA analysis. The book begins by discussing the value of DNA evidence and how to properly recognize, document, collect, and store it. The remaining chapters examine: The most widely adopted methods and the best practices for DNA isolation from forensic biological samples and human remainsStudies carried out on the use of both messenger RNA and small (micro) RNA profilingReal-time polymerase chain reaction (PCR) methods for quantification and assessment of human DNA prior to genotypingCapillary electr

This cross-disciplinary volume provides an overview of how complexity theory and the tools of statistical mechanics can be applied to linguistic problems to help reveal language groups, and to model the evolution and competition of languages in space and time. Illustrated with a series of case studies and worked examples, it presents an interdisciplinary framework to enable researchers from the mathematical, physical and social sciences to collaborate on linguistic problems. It demonstrates the complexity of linguistic databases and provides a mathematical toolkit for analyzing and extracting useful information from them - helping to conceptualize empirical facts better than a mere ethnographic view. Providing an important bridge to facilitate collaboration between linguists and mathematical modelers, this book will stimulate new ideas and avenues for research, and will form a valuable resource for advanced students and academics working across complex systems, sociolinguistics, and la

The goal of this text for students and professionals is to help readers who have worked with linear mixed models make the transition to generalized linear mixed models. Benefits and challenges of gene

This is an introductory textbook on spatial analysis and spatial statistics through GIS. Each chapter presents methods and metrics, explains how to interpret results, and provides worked examples. Topics include: describing and mapping data through exploratory spatial data analysis; analyzing geographic distributions and point patterns; spatial autocorrelation; spatial clustering; geographically weighted regression and OLS regression; and spatial econometrics. The worked examples link theory to practice through a single real-world case study, with software and illustrated guidance. Exercises are solved twice: first through ArcGIS, and then GeoDa. Through a simple methodological framework the book describes the dataset, explores spatial relations and associations, and builds models. Results are critically interpreted, and the advantages and pitfalls of using various spatial analysis methods are discussed. This is a valuable resource for graduate students and researchers analyzing geospa

This is an introductory textbook on spatial analysis and spatial statistics through GIS. Each chapter presents methods and metrics, explains how to interpret results, and provides worked examples. Topics include: describing and mapping data through exploratory spatial data analysis; analyzing geographic distributions and point patterns; spatial autocorrelation; spatial clustering; geographically weighted regression and OLS regression; and spatial econometrics. The worked examples link theory to practice through a single real-world case study, with software and illustrated guidance. Exercises are solved twice: first through ArcGIS, and then GeoDa. Through a simple methodological framework the book describes the dataset, explores spatial relations and associations, and builds models. Results are critically interpreted, and the advantages and pitfalls of using various spatial analysis methods are discussed. This is a valuable resource for graduate students and researchers analyzing geospa

Bringing together contributions on a diverse range of topics, this text explores the relationship between discrete and continuum mechanics as a tool to model new and complex metamaterials. Providing a comprehensive bibliography and historical review of the field, it covers mechanical, acoustic and pantographic metamaterials, discusses Naive Model Theory and Lagrangian discrete models, and their applications, and presents methods for pantographic structures and variational methods for multidisciplinary modeling and computation. The relationship between discrete and continuous models is discussed from both mathematical and engineering viewpoints, making the text ideal for those interested in the foundation of mechanics and computational applications, and innovative viewpoints on the use of discrete systems to model metamaterials are presented for those who want to go deeper into the field. An ideal text for graduate students and researchers interested in continuum approaches to the study

Responding to the developments of the past twenty years, Les Kirkup has thoroughly updated his popular book on experimental methods, while retaining the extensive coverage and practical advice from the first edition. Many topics from that edition remain, including keeping a record of work, how to deal with measurement uncertainties, understanding the statistical basis of data analysis and reporting the results of experiments. However, with new technologies influencing how experiments are devised, carried out, analyzed, presented and reported, this new edition reflects the digital changes which have taken place and the increased emphasis on the importance of communication skills in reporting results. Bringing together key elements of experimental methods into one coherent book, it is perfect for students seeking guidance with their experimental work, including how to acquire, analyse and present data. Exercises, worked examples and end-of-chapter problems are provided throughout the boo

Qualitative and Mixed Methods Data Analysis Using Dedoose®: A Practical Approach for Research Across the Social Sciences provides both new and experienced researchers with a guided introduction to dea

Using Stata for Statistical Analysis, Third Edition is a supplemental book for undergraduate and graduate level courses in research methods and statistical analysis where Stata is used. It can be appl

Qualitative Comparative Analysis in Mixed Methods Research and Evaluation provides a user-friendly introduction for using Qualitative Comparative Analysis (QCA) as part of a mixed methods approach to

During the last decades, freight transportation experienced a worldwide boom. At the same time, competition increased considerably, such that efficient cost structures are indispensable for any market

While there are numerous books on the analysis of Generalized Linear Models (GLMs), there is very little information available on how to design the experiments that will collect the data. This book wi

Recent Advances in System Reliability Engineering describes and evaluates the latest tools, techniques, strategies, and methods in this topic for a variety of applications. Special emphasis is put on

Statistical Methods for Overdispersed Count Data provides a review of the most recent methods and models for such data, including a description of R functions and packages that allow their implementat

This volume provides a practical introduction to the method of maximum likelihood as used in social science research. Ward and Ahlquist focus on applied computation in R and use real social science data from actual, published research. Unique among books at this level, it develops simulation-based tools for model evaluation and selection alongside statistical inference. The book covers standard models for categorical data as well as counts, duration data, and strategies for dealing with data missingness. By working through examples, math, and code, the authors build an understanding about the contexts in which maximum likelihood methods are useful and develop skills in translating mathematical statements into executable computer code. Readers will not only be taught to use likelihood-based tools and generate meaningful interpretations, but they will also acquire a solid foundation for continued study of more advanced statistical techniques.

A valuable new edition of a standard referenceThe use of statistical methods for categorical data has increased dramatically, particularly for applications in the biomedical and social sciences. An In

This book presents the methodology and mathematical models for dual-fuel coal-gas power plants in two basic configurations: systems coupled in parallel and in series.Dual-fuel gas and steam systems, e

This book offers an up-to-date, comprehensive coverage of stochastic dominance and its related concepts in a unified framework. A method for ordering probability distributions, stochastic dominance has grown in importance recently as a way to measure comparisons in welfare economics, inequality studies, health economics, insurance wages, and trade patterns. Whang pays particular attention to inferential methods and applications, citing and summarizing various empirical studies in order to relate the econometric methods with real applications and using computer codes to enable the practical implementation of these methods. Intuitive explanations throughout the book ensure that readers understand the basic technical tools of stochastic dominance.

This open access book provides innovative methods and original applications of sequence analysis (SA) and related methods for analysing longitudinal data describing life trajectories such as professio

This second edition provides detailed LC-MS(/MS) procedures for the analysis of compounds of clinical and toxicological significance. Chapters detail new and updated methods for analyzing drugs focusi

Planning Support Methods offers a practical quantitative guide to the key concepts and methods of urban and regional planning. The authors apply and critically assess the most important underlying for

Planning Support Methods offers a practical quantitative guide to the key concepts and methods of urban and regional planning. The authors apply and critically assess the most important underlying for

Most biological pathways, physical and neurological properties are highly conserved between humans and Drosophila and nearly 75% of human disease-causing genes have a functional homologue in Drosophil

Models and Methods for Youth and Young Adult Ministry is a rare book on young adult and youth ministry in that it weaves sound theology and solid pastoral practice. It invites pastoral practitioners,

GIS Tutorial for Crime Analysis, second edition, is a workbook for crime analysts and students of criminology. The book presents state-of-the-art methods that can be incorporated into any police depar