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Showing 23,526 through 23,550 of 23,817 results

Measuring and Modeling Health Care Costs (National Bureau of Economic Research Studies in Income and Wealth #76)

by Ana Aizcorbe Colin Baker Ernst R. Berndt David M. Cutler

Health care costs represent a nearly 18% of U.S. gross domestic product and 20% of government spending. While there is detailed information on where these health care dollars are spent, there is much less evidence on how this spending affects health. The research in Measuring and Modeling Health Care Costs seeks to connect our knowledge of expenditures with what we are able to measure of results, probing questions of methodology, changes in the pharmaceutical industry, and the shifting landscape of physician practice. The research in this volume investigates, for example, obesity’s effect on health care spending, the effect of generic pharmaceutical releases on the market, and the disparity between disease-based and population-based spending measures. This vast and varied volume applies a range of economic tools to the analysis of health care and health outcomes. Practical and descriptive, this new volume in the Studies in Income and Wealth series is full of insights relevant to health policy students and specialists alike.

Stated Preference Methods Using R (Chapman & Hall/CRC The R Series)

by Hideo Aizaki Tomoaki Nakatani Kazuo Sato

Stated Preference Methods Using R explains how to use stated preference (SP) methods, which are a family of survey methods, to measure people's preferences based on decision making in hypothetical choice situations. Along with giving introductory explanations of the methods, the book collates information on existing R functions and packages as well

High-Frequency Financial Econometrics

by Yacine Aït-Sahalia Jean Jacod

A comprehensive introduction to the statistical and econometric methods for analyzing high-frequency financial dataHigh-frequency trading is an algorithm-based computerized trading practice that allows firms to trade stocks in milliseconds. Over the last fifteen years, the use of statistical and econometric methods for analyzing high-frequency financial data has grown exponentially. This growth has been driven by the increasing availability of such data, the technological advancements that make high-frequency trading strategies possible, and the need of practitioners to analyze these data. This comprehensive book introduces readers to these emerging methods and tools of analysis.Yacine Aït-Sahalia and Jean Jacod cover the mathematical foundations of stochastic processes, describe the primary characteristics of high-frequency financial data, and present the asymptotic concepts that their analysis relies on. Aït-Sahalia and Jacod also deal with estimation of the volatility portion of the model, including methods that are robust to market microstructure noise, and address estimation and testing questions involving the jump part of the model. As they demonstrate, the practical importance and relevance of jumps in financial data are universally recognized, but only recently have econometric methods become available to rigorously analyze jump processes.Aït-Sahalia and Jacod approach high-frequency econometrics with a distinct focus on the financial side of matters while maintaining technical rigor, which makes this book invaluable to researchers and practitioners alike.

Statistics and the Evaluation of Evidence for Forensic Scientists (Statistics in Practice)

by Colin Aitken Franco Taroni Silvia Bozza

The leading resource in the statistical evaluation and interpretation of forensic evidence The third edition of Statistics and the Evaluation of Evidence for Forensic Scientists is fully updated to provide the latest research and developments in the use of statistical techniques to evaluate and interpret evidence. Courts are increasingly aware of the importance of proper evidence assessment when there is an element of uncertainty. Because of the increasing availability of data, the role of statistical and probabilistic reasoning is gaining a higher profile in criminal cases. That’s why lawyers, forensic scientists, graduate students, and researchers will find this book an essential resource, one which explores how forensic evidence can be evaluated and interpreted statistically. It’s written as an accessible source of information for all those with an interest in the evaluation and interpretation of forensic scientific evidence. Discusses the entire chain of reasoning–from evidence pre-assessment to court presentation; Includes material for the understanding of evidence interpretation for single and multiple trace evidence; Provides real examples and data for improved understanding. Since the first edition of this book was published in 1995, this respected series has remained a leading resource in the statistical evaluation of forensic evidence. It shares knowledge from authors in the fields of statistics and forensic science who are international experts in the area of evidence evaluation and interpretation. This book helps people to deal with uncertainty related to scientific evidence and propositions. It introduces a method of reasoning that shows how to update beliefs coherently and to act rationally. In this edition, readers can find new information on the topics of elicitation, subjective probabilities, decision analysis, and cognitive bias, all discussed in a Bayesian framework.

Implicit and Explicit Semantics Integration in Proof-Based Developments of Discrete Systems: Communications of NII Shonan Meetings

by Yamine Ait-Ameur Shin Nakajima Dominique Méry

This book addresses mechanisms for reducing model heterogeneity induced by the absence of explicit semantics expression in the formal techniques used to specify design models. More precisely, it highlights the advances in handling both implicit and explicit semantics in formal system developments, and discusses different contributions expressing different views and perceptions on the implicit and explicit semantics. The book is based on the discussions at the Shonan meeting on this topic held in 2016, and includes contributions from the participants summarising their perspectives on the problem and offering solutions. Divided into 5 parts: domain modelling, knowledge-based modelling, proof-based modelling, assurance cases, and refinement-based modelling, and offers inspiration for researchers and practitioners in the fields of formal methods, system and software engineering, domain knowledge modelling, requirement analysis, and explicit and implicit semantics of modelling languages.

Theoretical Studies on Extended Higgs Sectors Towards Future Precision Measurements (Springer Theses)

by Masashi Aiko

This book investigates the physics of the discovered Higgs boson and additional Higgs bosons in the extended Higgs models which includes higher-order quantum corrections. While the 125 GeV Higgs boson was discovered, the structure of the Higgs sector is still a mystery. Since the Higgs sector determines the concrete realization of the Higgs mechanism, the study of its nature is one of the central interests in current and future high-energy physics. The book begins with a review of the standard model and the two-Higgs doublet model, which is one of the representatives of the extended Higgs models. Subsequently, we discuss the studies of the two-Higgs doublet model at the lowest order of perturbation. Following the lowest-order analysis, we study the higher-order electroweak corrections in Higgs physics. After reviewing the renormalization procedure and the higher-order corrections in the decays of the discovered Higgs boson, we discuss the higher-order corrections in the Higgs strahlung process from an electron-positron collision, the decays of the additional charged and CP-odd Higgs bosons in the two-Higgs doublet model. From the series of these studies, it is found that the nature of the Higgs sector can be widely investigated by future collider experiments.

Psychological Testing and Assessment (12th edition)

by Lewis R. Aiken Gary Groth-Marnat

The aim of this text is to improve the knowledge, understanding, and practices of persons who construct tests, take tests, and ponder over the meaning and value of test scores. The emphasis is on psychological testing in educational, clinical, and industrial settings. Included is a detailed study guide divided among the 15 chapters and four appendices, as well as overviews, boldfaced terms and names, exercises, and, of course, tests. An MS-DOS diskette containing accompanying programs to construct, administer, and score tests can be obtained free of charge from the author. Annotation c. by Book News, Inc. , Portland, Or.

Fredholm and Local Spectral Theory II: With Application to Weyl-type Theorems (Lecture Notes in Mathematics #2235)

by Pietro Aiena

This monograph concerns the relationship between the local spectral theory and Fredholm theory of bounded linear operators acting on Banach spaces. The purpose of this book is to provide a first general treatment of the theory of operators for which Weyl-type or Browder-type theorems hold. The product of intensive research carried out over the last ten years, this book explores for the first time in a monograph form, results that were only previously available in journal papers. Written in a simple style, with sections and chapters following an easy, natural flow, it will be an invaluable resource for researchers in Operator Theory and Functional Analysis. The reader is assumed to be familiar with the basic notions of linear algebra, functional analysis and complex analysis.

Commodities, Energy and Environmental Finance (Fields Institute Communications #74)

by René Aïd Ronnie Sircar Michael Ludkovski

This volume is a collection of chapters covering the latest developments in applications of financial mathematics and statistics to topics in energy, commodity financial markets and environmental economics. The research presented is based on the presentations and discussions that took place during the Fields Institute Focus Program on Commodities, Energy and Environmental Finance in August 2013. The authors include applied mathematicians, economists and industry practitioners, providing for a multi-disciplinary spectrum of perspectives on the subject. The volume consists of four sections: Electricity Markets; Real Options; Trading in Commodity Markets; and Oligopolistic Models for Energy Production. Taken together, the chapters give a comprehensive summary of the current state of the art in quantitative analysis of commodities and energy finance. The topics covered include structural models of electricity markets, financialization of commodities, valuation of commodity real options, game-theory analysis of exhaustible resource management and analysis of commodity ETFs. The volume also includes two survey articles that provide a source for new researchers interested in getting into these topics.

Geometric Structures: An Inquiry-Based Approach for Prospective Elementary and Middle School Teachers

by Douglas Aichele John Wolfe

For prospective elementary and middle school teachers. This text provides a creative, inquiry-based experience with geometry that is appropriate for prospective elementary and middle school teachers. The coherent series of text activities supports each student’s growth toward being a confident, independent learner empowered with the help of peers to make sense of the geometric world. This curriculum is explicitly developed to provide future elementary and middle school teachers with experience recalling and appropriately using standard geometry ideas, experience learning and making sense of new geometry, experience discussing geometry with peers, experience asking questions about geometry, experience listening and understanding as others talk about geometry, experience gaining meaning from reading geometry, experience expressing geometry ideas through writing, experience thinking about geometry, and experience doing geometry. These activities constitute an “inquiry based” curriculum. In this style of learning and teaching, whole class discussions and group work replace listening to lectures as the dominant class activity.

Geometry: Explorations and Applications

by Douglas B. Aichele Patrick W Hopfensperger Miriam A. Leiva Marguerite M. Mason Stuart J. Murphy Vicki J. Schell Matthias C. Vheru

This book will help you use mathematics in your daily life and prepare you for success in future courses and careers.

Analysis of Deterministic Cyclic Gene Regulatory Network Models with Delays (SpringerBriefs in Electrical and Computer Engineering)

by Mehmet Eren Ahsen Hitay Özbay Silviu-Iulian Niculescu

This brief examines a deterministic, ODE-based model for gene regulatory networks (GRN) that incorporates nonlinearities and time-delayed feedback. An introductory chapter provides some insights into molecular biology and GRNs. The mathematical tools necessary for studying the GRN model are then reviewed, in particular Hill functions and Schwarzian derivatives. One chapter is devoted to the analysis of GRNs under negative feedback with time delays and a special case of a homogenous GRN is considered. Asymptotic stability analysis of GRNs under positive feedback is then considered in a separate chapter, in which conditions leading to bi-stability are derived. Graduate and advanced undergraduate students and researchers in control engineering, applied mathematics, systems biology and synthetic biology will find this brief to be a clear and concise introduction to the modeling and analysis of GRNs.

Normal and Student´s t Distributions and Their Applications

by Mohammad Ahsanullah B. M. Golam Kibria Mohammad Shakil

The most important properties of normal and Student t-distributions are presented. A number of applications of these properties are demonstrated. New related results dealing with the distributions of the sum, product and ratio of the independent normal and Student distributions are presented. The materials will be useful to the advanced undergraduate and graduate students and practitioners in the various fields of science and engineering.

Characterizations of Univariate Continuous Distributions (Atlantis Studies in Probability and Statistics #7)

by Mohammad Ahsanullah

Provides in an organized manner characterizations of univariate probability distributions with many new results published in this area since the 1978 work of Golambos & Kotz "Characterizations of Probability Distributions" (Springer), together with applications of the theory in model fitting and predictions.

The Potential of Fields in Einstein's Theory of Gravitation

by Zafar Ahsan

This book presents a detailed study of the Lanczos potential in general relativity by using tetrad formalisms. It demonstrates that these formalisms offer some simplifications over the tensorial methods, and investigates a general approach to finding the Lanczos potential for algebraic space–time by translating all the tensorial relations concerning the Lanczos potential into the language of tetrad formalisms and using the Newman–Penrose and Geroch–Held–Penrose formalisms. In addition, the book obtains the Lanczos potential for perfect fluid space–time, and applies the results to cosmological models of the universe. In closing, it highlights other methods, apart from tetrad formalisms, for finding the Lanczos potential, as well as further applications of the Newman–Penrose formalism. Given its scope, the book will be of interest to pure mathematicians, theoretical physicists and cosmologists, and will provide common ground for communication among these scientific communities.

Advances in Social Simulation: Proceedings of the 15th Social Simulation Conference: 23–27 September 2019 (Springer Proceedings in Complexity)

by Petra Ahrweiler Martin Neumann

This book presents the state of the art in social simulation as presented at the Social Simulation Conference 2019 in Mainz, Germany. It covers the developments in applications and methods of social simulation, addressing societal issues such as socio-ecological systems and policymaking. Methodological issues discussed include large-scale empirical calibration, model sharing and interdisciplinary research, as well as decision-making models, validation and the use of qualitative data in simulation modeling. Research areas covered include archaeology, cognitive science, economics, organization science and social simulation education.This book gives readers insight into the increasing use of social simulation in both its theoretical development and in practical applications such as policymaking whereby modeling and the behavior of complex systems is key. The book appeals to students, researchers and professionals in the various fields.

Foundational and Applied Statistics for Biologists Using R

by Ken A. Aho

Full of biological applications, exercises, and interactive graphical examples, Foundational and Applied Statistics for Biologists Using R presents comprehensive coverage of both modern analytical methods and statistical foundations. The author harnesses the inherent properties of the R environment to enable students to examine the code of complica

Post-Shrinkage Strategies in Statistical and Machine Learning for High Dimensional Data

by Syed Ejaz Ahmed Feryaal Ahmed Bahadir Yüzbaşı

This book presents some post-estimation and predictions strategies for the host of useful statistical models with applications in data science. It combines statistical learning and machine learning techniques in a unique and optimal way. It is well-known that machine learning methods are subject to many issues relating to bias, and consequently the mean squared error and prediction error may explode. For this reason, we suggest shrinkage strategies to control the bias by combining a submodel selected by a penalized method with a model with many features. Further, the suggested shrinkage methodology can be successfully implemented for high dimensional data analysis. Many researchers in statistics and medical sciences work with big data. They need to analyse this data through statistical modelling. Estimating the model parameters accurately is an important part of the data analysis. This book may be a repository for developing improve estimation strategies for statisticians. This book will help researchers and practitioners for their teaching and advanced research, and is an excellent textbook for advanced undergraduate and graduate courses involving shrinkage, statistical, and machine learning. The book succinctly reveals the bias inherited in machine learning method and successfully provides tools, tricks and tips to deal with the bias issue. Expertly sheds light on the fundamental reasoning for model selection and post estimation using shrinkage and related strategies. This presentation is fundamental, because shrinkage and other methods appropriate for model selection and estimation problems and there is a growing interest in this area to fill the gap between competitive strategies. Application of these strategies to real life data set from many walks of life. Analytical results are fully corroborated by numerical work and numerous worked examples are included in each chapter with numerous graphs for data visualization. The presentation and style of the book clearly makes it accessible to a broad audience. It offers rich, concise expositions of each strategy and clearly describes how to use each estimation strategy for the problem at hand. This book emphasizes that statistics/statisticians can play a dominant role in solving Big Data problems, and will put them on the precipice of scientific discovery. The book contributes novel methodologies for HDDA and will open a door for continued research in this hot area. The practical impact of the proposed work stems from wide applications. The developed computational packages will aid in analyzing a broad range of applications in many walks of life.

Composing Fisher Kernels from Deep Neural Models: A Practitioner's Approach (SpringerBriefs in Computer Science)

by Sarah Ahmed Tayyaba Azim

This book shows machine learning enthusiasts and practitioners how to get the best of both worlds by deriving Fisher kernels from deep learning models. In addition, the book shares insight on how to store and retrieve large-dimensional Fisher vectors using feature selection and compression techniques. Feature selection and feature compression are two of the most popular off-the-shelf methods for reducing data’s high-dimensional memory footprint and thus making it suitable for large-scale visual retrieval and classification. Kernel methods long remained the de facto standard for solving large-scale object classification tasks using low-level features, until the revival of deep models in 2006. Later, they made a comeback with improved Fisher vectors in 2010. However, their supremacy was always challenged by various versions of deep models, now considered to be the state of the art for solving various machine learning and computer vision tasks. Although the two research paradigms differ significantly, the excellent performance of Fisher kernels on the Image Net large-scale object classification dataset has caught the attention of numerous kernel practitioners, and many have drawn parallels between the two frameworks for improving the empirical performance on benchmark classification tasks. Exploring concrete examples on different data sets, the book compares the computational and statistical aspects of different dimensionality reduction approaches and identifies metrics to show which approach is superior to the other for Fisher vector encodings. It also provides references to some of the most useful resources that could provide practitioners and machine learning enthusiasts a quick start for learning and implementing a variety of deep learning models and kernel functions.

Matrices, Statistics and Big Data: Selected Contributions from IWMS 2016 (Contributions to Statistics)

by S. Ejaz Ahmed Francisco Carvalho Simo Puntanen

This volume features selected, refereed papers on various aspects of statistics, matrix theory and its applications to statistics, as well as related numerical linear algebra topics and numerical solution methods, which are relevant for problems arising in statistics and in big data. The contributions were originally presented at the 25th International Workshop on Matrices and Statistics (IWMS 2016), held in Funchal (Madeira), Portugal on June 6-9, 2016. The IWMS workshop series brings together statisticians, computer scientists, data scientists and mathematicians, helping them better understand each other’s tools, and fostering new collaborations at the interface of matrix theory and statistics.

Penalty, Shrinkage and Pretest Strategies

by S. Ejaz Ahmed

The objective of this book is to compare the statistical properties of penalty and non-penalty estimation strategies for some popular models. Specifically, it considers the full model, submodel, penalty, pretest and shrinkage estimation techniques for three regression models before presenting the asymptotic properties of the non-penalty estimators and their asymptotic distributional efficiency comparisons. Further, the risk properties of the non-penalty estimators and penalty estimators are explored through a Monte Carlo simulation study. Showcasing examples based on real datasets, the book will be useful for students and applied researchers in a host of applied fields. The book's level of presentation and style make it accessible to a broad audience. It offers clear, succinct expositions of each estimation strategy. More importantly, it clearly describes how to use each estimation strategy for the problem at hand. The book is largely self-contained, as are the individual chapters, so that anyone interested in a particular topic or area of application may read only that specific chapter. The book is specially designed for graduate students who want to understand the foundations and concepts underlying penalty and non-penalty estimation and its applications. It is well-suited as a textbook for senior undergraduate and graduate courses surveying penalty and non-penalty estimation strategies, and can also be used as a reference book for a host of related subjects, including courses on meta-analysis. Professional statisticians will find this book to be a valuable reference work, since nearly all chapters are self-contained.

Measure-Valued Solutions for Nonlinear Evolution Equations on Banach Spaces and Their Optimal Control

by N. U. Ahmed Shian Wang

This book offers the first comprehensive presentation of measure-valued solutions for nonlinear deterministic and stochastic evolution equations on infinite dimensional Banach spaces. Unlike traditional solutions, measure-valued solutions allow for a much broader class of abstract evolution equations to be addressed, providing a broader approach.The book presents extensive results on the existence of measure-valued solutions for differential equations that have no solutions in the usual sense. It covers a range of topics, including evolution equations with continuous/discontinuous vector fields, neutral evolution equations subject to vector measures as impulsive forces, stochastic evolution equations, and optimal control of evolution equations. The optimal control problems considered cover the existence of solutions, necessary conditions of optimality, and more, significantly complementing the existing literature.This book will be of great interest to researchers in functional analysis, partial differential equations, dynamic systems and their optimal control, and their applications, advancing previous research and providing a foundation for further exploration of the field.

Cybersecurity for Smart Cities: Practices and Challenges (Advanced Sciences and Technologies for Security Applications)

by Mohiuddin Ahmed Paul Haskell-Dowland

Ensuring cybersecurity for smart cities is crucial for a sustainable cyber ecosystem. Given the undeniable complexity of smart cities, fundamental issues such as device configurations and software updates should be addressed when it is most needed to fight cyber-crime and ensure data privacy. This book addresses the cybersecurity challenges associated with smart cities, aiming to provide a bigger picture of the concepts, intelligent techniques, practices and research directions in this area. Furthermore, this book serves as a single source of reference for acquiring knowledge on the technology, processes and people involved in the next-generation of cyber-smart cities.

Fuzzy Logic Based Power-Efficient Real-Time Multi-Core System

by Jameel Ahmed Mohammed Yakoob Siyal Shaheryar Najam Zohaib Najam

This book focuses on identifying the performance challenges involved in computer architectures, optimal configuration settings and analysing their impact on the performance of multi-core architectures. Proposing a power and throughput-aware fuzzy-logic-based reconfiguration for Multi-Processor Systems on Chip (MPSoCs) in both simulation and real-time environments, it is divided into two major parts. The first part deals with the simulation-based power and throughput-aware fuzzy logic reconfiguration for multi-core architectures, presenting the results of a detailed analysis on the factors impacting the power consumption and performance of MPSoCs. In turn, the second part highlights the real-time implementation of fuzzy-logic-based power-efficient reconfigurable multi-core architectures for Intel and Leone3 processors.

Foundations of Software Engineering

by Ashfaque Ahmed Bhanu Prasad

The best way to learn software engineering is by understanding its core and peripheral areas. Foundations of Software Engineering provides in-depth coverage of the areas of software engineering that are essential for becoming proficient in the field. The book devotes a complete chapter to each of the core areas. Several peripheral areas are also explained by assigning a separate chapter to each of them. Rather than using UML or other formal notations, the content in this book is explained in easy-to-understand language. Basic programming knowledge using an object-oriented language is helpful to understand the material in this book. The knowledge gained from this book can be readily used in other relevant courses or in real-world software development environments.This textbook educates students in software engineering principles. It covers almost all facets of software engineering, including requirement engineering, system specifications, system modeling, system architecture, system implementation, and system testing. Emphasizing practical issues, such as feasibility studies, this book explains how to add and develop software requirements to evolve software systems.This book was written after receiving feedback from several professors and software engineers. What resulted is a textbook on software engineering that not only covers the theory of software engineering but also presents real-world insights to aid students in proper implementation. Students learn key concepts through carefully explained and illustrated theories, as well as concrete examples and a complete case study using Java. Source code is also available on the book’s website. The examples and case studies increase in complexity as the book progresses to help students build a practical understanding of the required theories and applications.

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