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Both state-space models and Markov switching models have been highly productive paths for empirical research in macroeconomics and finance. This book presents recent advances in econometric methods that make feasible the estimation of models that have both features. One approach, in the classical framework, approximates the likelihood function; the other, in the Bayesian framework, uses Gibbs-sampling to simulate posterior distributions from data.The authors present numerous applications of these approaches in detail: decomposition of time series into trend and cycle, a new index of coincident economic indicators, approaches to modeling monetary policy uncertainty, Friedman's "plucking" model of recessions, the detection of turning points in the business cycle and the question of whether booms and recessions are duration-dependent, state-space models with heteroskedastic disturbances, fads and crashes in financial markets, long-run real exchange rates, and mean reversion in asset returns.

Both state-space models and Markov switching models have been highly productive paths for empirical research in macroeconomics and finance. This book presents recent advances in econometric methods that make feasible the estimation of models that have both features. One approach, in the classical framework, approximates the likelihood function; the other, in the Bayesian framework, uses Gibbs-sampling to simulate posterior distributions from data.The authors present numerous applications of these approaches in detail: decomposition of time series into trend and cycle, a new index of coincident economic indicators, approaches to modeling monetary policy uncertainty, Friedman's "plucking" model of recessions, the detection of turning points in the business cycle and the question of whether booms and recessions are duration-dependent, state-space models with heteroskedastic disturbances, fads and crashes in financial markets, long-run real exchange rates, and mean reversion in asset returns.

Both state-space models and Markov switching models have been highly productive paths for empirical research in macroeconomics and finance. This book presents recent advances in econometric methods that make feasible the estimation of models that have both features. One approach, in the classical framework, approximates the likelihood function; the other, in the Bayesian framework, uses Gibbs-sampling to simulate posterior distributions from data.The authors present numerous applications of these approaches in detail: decomposition of time series into trend and cycle, a new index of coincident economic indicators, approaches to modeling monetary policy uncertainty, Friedman's "plucking" model of recessions, the detection of turning points in the business cycle and the question of whether booms and recessions are duration-dependent, state-space models with heteroskedastic disturbances, fads and crashes in financial markets, long-run real exchange rates, and mean reversion in asset returns.

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Reviews sampling methods used in surveys: simple random sampling, systematic sampling, stratification, cluster and multi-stage sampling, sampling with probability proportional to size, two-phase sampling, replicated sampling, panel designs, and non-probability sampling. Kalton discusses issues of practical implementation, including frame problems and non-response, and gives examples of sample designs for a national face-to-face interview survey and for a telephone survey. He also treats the use of weights in survey analysis, the computation of sampling errors with complex sampling designs, and the determination of sample size.

This book provides a comprehensive account of the important field of aerosol sampling as it is applied to the measurement of aerosols that are ubiquitous in occupational and living environments, both indoor and outdoor. It is written in four parts: Part A contains 9 chapters that describe the current knowledge of the physical science that underpins the process of aerosol sampling. Part B contains 4 chapters, which present the basis of standards for aerosols, including the link with human exposure by inhalation. Part C contains 7 chapters that cover the development of practical aerosol sampling instrumentation, and how technical designs and methods have evolved over the years in order that aerosol sampling may be carried out in a manner matching the health-related and other criteria that have been proposed as parts of standards. Finally Part D contains 6 chapters that describe how a wide range of aerosol sampling instruments have performed when they have been applied in the field in both occupational and ambient atmospheric environments, including how different instruments, nominally intended to measure the same aerosol fraction, compare when used side-by-side in the real world. The book draws together all that is known about aerosol sampling, for the benefit of researchers and practitioners in occupational and environmental health and all other fields of science and engineering where aerosols are of interest.

This is a hard cover book: Used - Acceptable: All pages and the cover are intact, but shrink wrap, dust covers, or boxed set case may be missing. Pages may include limited notes, highlighting, or minor water damage but the text is readable. Item may be missing bundled media.

This book provides a comprehensive account of the important field of aerosol sampling as it is applied to the measurement of aerosols that are ubiquitous in occupational and living environments, both indoor and outdoor. It is written in four parts: Part A contains 9 chapters that describe the current knowledge of the physical science that underpins the process of aerosol sampling. Part B contains 4 chapters, which present the basis of standards for aerosols, including the link with human exposure by inhalation. Part C contains 7 chapters that cover the development of practical aerosol sampling instrumentation, and how technical designs and methods have evolved over the years in order that aerosol sampling may be carried out in a manner matching the health-related and other criteria that have been proposed as parts of standards. Finally Part D contains 6 chapters that describe how a wide range of aerosol sampling instruments have performed when they have been applied in the field in both occupational and ambient atmospheric environments, including how different instruments, nominally intended to measure the same aerosol fraction, compare when used side-by-side in the real world. The book draws together all that is known about aerosol sampling, for the benefit of researchers and practitioners in occupational and environmental health and all other fields of science and engineering where aerosols are of interest.

The second in a two-volume series on signal analysis, this book draws on the foundations laid in the first volume to survey the diverse applications of sampling theory both within mathematics and in other areas of science. Many of the topics included are appearing for the first time in a book, and the book seeks to bring readers to the forefront of research. Topics include combinatorial analysis, number theory, neural networks, derivative sampling, wavelets, stochastic signals, random fields, and abstract harmonic analysis.

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The second in a two-volume series on signal analysis, this book draws on the foundations laid in the first volume to survey the diverse applications of sampling theory both within mathematics and in other areas of science. Many of the topics included are appearing for the first time in a book, and the book seeks to bring readers to the forefront of research. Topics include combinatorial analysis, number theory, neural networks, derivative sampling, wavelets, stochastic signals, random fields, and abstract harmonic analysis.

Advances in Shannon's Sampling Theory provides an up-to-date discussion of sampling theory, emphasizing the interaction between sampling theory and other branches of mathematical analysis, including the theory of boundary-value problems, frames, wavelets, multiresolution analysis, special functions, and functional analysis. The author not only traces the history and development of the theory, but also presents original research and results that have never before appeared in book form. Recent techniques covered include the Feichtinger-Gröchenig sampling theory; frames, wavelets, multiresolution analysis and sampling; boundary-value problems and sampling theorems; and special functions and sampling theorems. The book will interest graduate students and professionals in electrical engineering, communications, and applied mathematics.

With much material not previously found in book form, this book fills a gap by discussing the equivalence of signal functions with their sets of values taken at discreet points comprehensively and on a firm mathematical ground. The wide variety of topics begins with an introduction to the main ideas and background material on Fourier analysis and Hilbert spaces and their bases. Other chapters discuss sampling of Bernstein and Paley-Wiener spaces; Kramer's Lemma and its application to eigenvalue problems; contour integral methods including a proof of the equivalence of the sampling theory; the Poisson summation formula and Cauchy's integral formula; optimal regular, irregular, multi-channel, multi-band and multi-dimensional sampling; and Campbell's generalized sampling theorem. Mathematicians, physicists, and communications engineers will welcome the scope of information found here.

Advances in Shannon's Sampling Theory provides an up-to-date discussion of sampling theory, emphasizing the interaction between sampling theory and other branches of mathematical analysis, including the theory of boundary-value problems, frames, wavelets, multiresolution analysis, special functions, and functional analysis. The author not only traces the history and development of the theory, but also presents original research and results that have never before appeared in book form. Recent techniques covered include the Feichtinger-Gröchenig sampling theory; frames, wavelets, multiresolution analysis and sampling; boundary-value problems and sampling theorems; and special functions and sampling theorems. The book will interest graduate students and professionals in electrical engineering, communications, and applied mathematics.

With much material not previously found in book form, this book fills a gap by discussing the equivalence of signal functions with their sets of values taken at discreet points comprehensively and on a firm mathematical ground. The wide variety of topics begins with an introduction to the main ideas and background material on Fourier analysis and Hilbert spaces and their bases. Other chapters discuss sampling of Bernstein and Paley-Wiener spaces; Kramer's Lemma and its application to eigenvalue problems; contour integral methods including a proof of the equivalence of the sampling theory; the Poisson summation formula and Cauchy's integral formula; optimal regular, irregular, multi-channel, multi-band and multi-dimensional sampling; and Campbell's generalized sampling theorem. Mathematicians, physicists, and communications engineers will welcome the scope of information found here.

ENVIRONMENTAL ETHICS, 7th Edition presents the main issues in environmental ethics using a diverse set of readings arranged in dialogue format. The seventh edition of this popular anthology features selections from contemporary authors as well as readings from classic writers, all chosen for their clarity and accessibility. By exploring both sides of every topic, this edition helps students quickly grasp each subject and move from theory to application. Making this textbook even more enjoyable to read include new sections on Environmental Justice, Climate Change, Food Ethics, Nature and Naturalness, Sustainability, Population and Consumption, Future Generations, and Holism.

Classic Grounded Theory: Applications With Qualitative and Quantitative Data provides practical “how to” guidance for doing grounded theory (GT) using the classic approach articulated by Barney Glaser. Authors Judith A. Holton and Isabelle Walsh emphasize the philosophical flexibility of classic GT as a “full package” approach that can be applied to any study and any type of data where the goal is to discover and generate a conceptually integrated theory. Drawing on the experiences of novice researchers who have participated in GT troubleshooting seminars, the book provides step-by-step guidance on undertaking a research study that stays true to the classic GT practice paradigm.  

Family Theories: Foundations and Applications presents a comprehensive and accessible approach to the most current perspectives in the field of family theory. Integrates classic and contemporary writings on family theories Features compelling case studies drawn from the authors’ experiences working with thousands of students Represents an integrative use of theory, research, and practice Utilizes the metaphor of “developing your theory app” to translate complex academic ideas into accessible, student-friendly language

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Turing's famous 1936 paper introduced a formal definition of a computing machine, a Turing machine. This model led to both the development of actual computers and to computability theory, the study of what machines can and cannot compute. This book presents classical computability theory from Turing and Post to current results and methods, and their use in studying the information content of algebraic structures, models, and their relation to Peano arithmetic. The author presents the subject as an art to be practiced, and an art in the aesthetic sense of inherent beauty which all mathematicians recognize in their subject. Part I gives a thorough development of the foundations of computability, from the definition of Turing machines up to finite injury priority arguments. Key topics include relative computability, and computably enumerable sets, those which can be effectively listed but not necessarily effectively decided, such as the theorems of Peano arithmetic. Part II includes the study of computably open and closed sets of reals and basis and nonbasis theorems for effectively closed sets. Part III covers minimal Turing degrees. Part IV is an introduction to games and their use in proving theorems. Finally, Part V offers a short history of computability theory.The author has honed the content over decades according to feedback from students, lecturers, and researchers around the world. Most chapters include exercises, and the material is carefully structured according to importance and difficulty. The book is suitable for advanced undergraduate and graduate students in computer science and mathematics and researchers engaged with computability and mathematical logic.