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The Distribution of Income and Wealth: Parametric Modeling with the κ-Generalized Family, Clementi Fabio, Gallegati Mauro


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Автор: Clementi Fabio, Gallegati Mauro
Название:  The Distribution of Income and Wealth: Parametric Modeling with the κ-Generalized Family
ISBN: 9783319801353
Издательство: Springer
Классификация:






ISBN-10: 331980135X
Обложка/Формат: Paperback
Страницы: 177
Вес: 0.28 кг.
Дата издания: 30.03.2018
Серия: New economic windows
Язык: English
Издание: Softcover reprint of
Иллюстрации: 24 illustrations, black and white; xvi, 177 p. 24 illus.
Размер: 23.39 x 15.60 x 1.07 cm
Читательская аудитория: General (us: trade)
Подзаголовок: Parametric modeling with the -generalized family
Ссылка на Издательство: Link
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Поставляется из: Германии
Описание: This book presents a systematic overview of cutting-edge research in the field of parametric modeling of personal income and wealth distribution, which allows one to represent how income/wealth is distributed within a given population.


Parametric Interval Algebraic Systems

Автор: Skalna
Название: Parametric Interval Algebraic Systems
ISBN: 3319751867 ISBN-13(EAN): 9783319751863
Издательство: Springer
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Цена: 13974.00 р.
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Описание: This self-contained book presents a framework for solving a general class of linear systems with coefficients being continuous functions of parameters varying within prescribed intervals.

Parametric Resonance in Dynamical Systems

Автор: Thor I. Fossen; Henk Nijmeijer
Название: Parametric Resonance in Dynamical Systems
ISBN: 1489996427 ISBN-13(EAN): 9781489996428
Издательство: Springer
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Цена: 20896.00 р.
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Описание: This volume discusses parametric resonance and its occurrence in mechanical systems including those found in road, air and seagoing vehicles. It introduces the root causes of PR as well as its mathematical interpretation via the Mathieu-Hill equation.

Parametric Interval Algebraic Systems

Автор: Iwona Skalna
Название: Parametric Interval Algebraic Systems
ISBN: 3319892878 ISBN-13(EAN): 9783319892870
Издательство: Springer
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Цена: 13974.00 р.
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Описание: This self-contained book presents a framework for solving a general class of linear systems with coefficients being continuous functions of parameters varying within prescribed intervals. It also provides a comprehensive overview of the theory related to solving parametric interval linear systems and the basic properties of parametric interval matrices. In particular, it develops several new algorithms delivering sharp rigorous bounds for the solutions of such systems with full mathematical rigor. The framework employs the arithmetic of revised affine forms that enables the readers to handle dependent data. The book is intended not only for researchers interested in developing rigorous methods of numerical linear algebra, but also for engineers dealing with problems involving uncertain data. The theory discussed is also useful in various other fields of numerical analysis, in computer graphics, economics, computational geometry, computer-aided design, computer-assisted proofs, computer graphics, control theory, solving constraint satisfaction problems, and global optimization.

Combined Parametric-Nonparametric Identification of Block-Oriented Systems

Автор: Grzegorz Mzyk
Название: Combined Parametric-Nonparametric Identification of Block-Oriented Systems
ISBN: 3319035959 ISBN-13(EAN): 9783319035956
Издательство: Springer
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Цена: 14365.00 р.
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Описание: This volume introduces a variety of combined parametric-nonparametric algorithms aimed at resolving problems with block-oriented non-linear dynamic system identification in the presence of random disturbances. It includes analysis of their limit properties.

Nonlinear Time Series / Nonparametric and Parametric Methods

Автор: Fan Jianqing, Yao Qiwei
Название: Nonlinear Time Series / Nonparametric and Parametric Methods
ISBN: 0387261427 ISBN-13(EAN): 9780387261423
Издательство: Springer
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Цена: 15372.00 р.
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Описание: This book presents the contemporary statistical methods and theory of nonlinear time series analysis. The principal focus is on nonparametric and semiparametric techniques developed in the last decade. It covers the techniques for modelling in state-space, in frequency-domain as well as in time-domain. To reflect the integration of parametric and nonparametric methods in analyzing time series data, the book also presents an up-to-date exposure of some parametric nonlinear models, including ARCH/GARCH models and threshold models. A compact view on linear ARMA models is also provided. Data arising in real applications are used throughout to show how nonparametric approaches may help to reveal local structure in high-dimensional data. Important technical tools are also introduced. The book will be useful for graduate students, application-oriented time series analysts, and new and experienced researchers. It will have the value both within the statistical community and across a broad spectrum of other fields such as econometrics, empirical finance, population biology and ecology. The prerequisites are basic courses in probability and statistics. Jianqing Fan, coauthor of the highly regarded book Local Polynomial Modeling, is Professor of Statistics at the University of North Carolina at Chapel Hill and the Chinese University of Hong Kong. His published work on nonparametric modeling, nonlinear time series, financial econometrics, analysis of longitudinal data, model selection, wavelets and other aspects of methodological and theoretical statistics has been recognized with the Presidents' Award from the Committee of Presidents of Statistical Societies, the Hettleman Prize for Artistic and Scholarly Achievement from the University of North Carolina, and by his election as a fellow of the American Statistical Association and the Institute of Mathematical Statistics. Qiwei Yao is Professor of Statistics at the London School of Economics and Political Science. He is an elected member of the International Statistical Institute, and has served on the editorial boards for the Journal of the Royal Statistical Society (Series B) and the Australian and New Zealand Journal of Statistics.

Stable Parametric Programming

Автор: S. Zlobec
Название: Stable Parametric Programming
ISBN: 0792371399 ISBN-13(EAN): 9780792371397
Издательство: Springer
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Цена: 19564.00 р.
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Описание: Optimality and stability are two important notions in applied mathematics. This book is a study of these notions and their relationship in linear and convex parametric programming models. Written in an analytic spirit, it begins with a survey of basic optimality conditions in nonlinear programming.

Non-parametric Tuning of PID Controllers

Автор: Igor Boiko
Название: Non-parametric Tuning of PID Controllers
ISBN: 1447160460 ISBN-13(EAN): 9781447160465
Издательство: Springer
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Цена: 15372.00 р.
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Описание: This book joins new modifications of classical relay feedback test with application-specific optimal tuning rules to form a non-parametric test-and-tuning method. Includes problems of optimization and identification accompanied by downloadable MATLAB (R) code.

Income and Wealth Distribution, Inequality and Poverty

Автор: Camilo Dagum; Michele Zenga
Название: Income and Wealth Distribution, Inequality and Poverty
ISBN: 3540528636 ISBN-13(EAN): 9783540528630
Издательство: Springer
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Цена: 18167.00 р.
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Описание: Provides an up-to-date theoretical discussion with applications of the issue of income distribution models, income inequality measurement, decomposition and inference, and the basic issue of the source and reliability of income and wealth distribution statistics.

Distribution of Income and Wealth in Ontario: Theory and Evidence

Автор: Beach Charles M., Flatters Frank, Card David E.
Название: Distribution of Income and Wealth in Ontario: Theory and Evidence
ISBN: 0802033695 ISBN-13(EAN): 9780802033697
Издательство: Wiley
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Цена: 12397.00 р.
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Описание: This book provides an extensive survey of recent literature and a new source of income and wealth distribution data for Ontario, drawn from newly available microdata sets. It also presents an evaluation of the data as a basis for measuring inequality in the distribution of economic and well-being.

Distributed Transmission-Distribution Coordinated Energy Management Based on Generalized Master-Slave Splitting Theory

Автор: Zhengshuo Li
Название: Distributed Transmission-Distribution Coordinated Energy Management Based on Generalized Master-Slave Splitting Theory
ISBN: 9811356874 ISBN-13(EAN): 9789811356872
Издательство: Springer
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Цена: 13974.00 р.
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Описание: To ensure the security and economy of future power system operation in the context of a high degree of renewable energy penetration, this thesis proposes a new distributed algorithm called generalized master-slave-splitting (G-MSS) theory and a new transmission-distribution coordinated energy management (TDCEM) method that is based on the G-MSS theory.The thesis studies the mathematical properties of the G-MSS theory in detail. Based on the G-MSS theory, a distributed TDCEM method – which involves distributed security analysis, distributed voltage stability analysis, distributed economic dispatch and distributed optimal power flow for an integrated transmission-distribution system – is then developed for the first time. The thesis demonstrates that the proposed TDCEM method significantly contributes to more reliable and optimal operation in power systems. The book will benefit researchers, scientists and engineers in the field of power system operation and optimization.


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