Nonparametric Methods in Change Point Problems, E. Brodsky; B.S. Darkhovsky

Автор: Brodsky, E., Darkhovsky, B.S.
Название: Nonparametric Methods in Change Point Problems
ISBN: 0792321227 ISBN-13(EAN): 9780792321224
Издательство: Springer
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Цена: 88500.00 T
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Описание: This volume deals with non-parametric methods of change point (disorder) detection in random processes and fields. A systematic account is given of up-to-date developments in this rapidly evolving branch of statistics.

Автор: Racine, Jeffrey; Su, Liangjun; Ullah, Aman
Название: The Oxford Handbook of Applied Nonparametric and Semiparametric Econometrics and Statistics
ISBN: 0199857946 ISBN-13(EAN): 9780199857944
Издательство: Oxford Academ
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Цена: 153120.00 T
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Описание: This volume, edited by Jeffrey Racine, Liangjun Su, and Aman Ullah, contains the latest research on nonparametric and semiparametric econometrics and statistics. Chapters by leading international econometricians and statisticians highlight the interface between econometrics and statistical methods for nonparametric and semiparametric procedures.

Автор: Henderson
Название: Applied Nonparametric Econometrics
ISBN: 0521279682 ISBN-13(EAN): 9780521279680
Издательство: Cambridge Academ
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Цена: 44350.00 T
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Описание: The majority of empirical research in economics ignores the potential benefits of nonparametric methods, while the majority of advances in nonparametric theory ignore the problems faced in applied econometrics. This book helps bridge this gap between applied economists and theoretical nonparametric econometricians, discussing basic to advanced nonparametric methods with applications.

Автор: Ghosal, Subhashis.
Название: Fundamentals of Nonparametric Bayesian Inference
ISBN: 0521878268 ISBN-13(EAN): 9780521878265
Издательство: Cambridge Academ
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Цена: 86590.00 T
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Описание: Written by top researchers, this self-contained text is the authoritative account of Bayesian nonparametrics, a nearly universal framework for inference in statistics and machine learning, with practical use in all areas of science, including economics and biostatistics. Appendices with prerequisites and numerous exercises support its use for graduate courses.

Автор: Muller, P., Quintana, F.A., Jara, A., Hanson, T.
Название: Bayesian Nonparametric Data Analysis
ISBN: 3319189670 ISBN-13(EAN): 9783319189673
Издательство: Springer
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Цена: 79190.00 T
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Описание: This book reviews nonparametric Bayesian methods and models that have proven useful in the context of data analysis. In selecting specific nonparametric models, simpler and more traditional models are favored over specialized ones.

Автор: Alexandre B. Tsybakov
Название: Introduction to Nonparametric Estimation
ISBN: 0387790519 ISBN-13(EAN): 9780387790510
Издательство: Springer
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Цена: 102480.00 T
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Описание: Presents basic nonparametric regression and density estimators and analyzes their properties. This book covers minimax lower bounds, and develops advanced topics such as: Pinsker`s theorem, oracle inequalities, Stein shrinkage, and sharp minimax adaptivity.

Автор: Liu
Название: Robust Rank-Based and Nonparametric Methods
ISBN: 3319390635 ISBN-13(EAN): 9783319390635
Издательство: Springer
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Цена: 102480.00 T
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Описание: The contributors to this volume include many of the distinguished researchers in this area. Many of these scholars have collaborated with Joseph McKean to develop underlying theory for these methods, obtain small sample corrections, and develop efficient algorithms for their computation. The papers cover the scope of the area, including robust nonparametric rank-based procedures through Bayesian and big data rank-based analyses. Areas of application include biostatistics and spatial areas. Over the last 30 years, robust rank-based and nonparametric methods have developed considerably. These procedures generalize traditional Wilcoxon-type methods for one- and two-sample location problems. Research into these procedures has culminated in complete analyses for many of the models used in practice including linear, generalized linear, mixed, and nonlinear models. Settings are both multivariate and univariate. With the development of R packages in these areas, computation of these procedures is easily shared with readers and implemented. This book is developed from the International Conference on Robust Rank-Based and Nonparametric Methods, held at Western Michigan University in April 2015.

Автор: Samaniego Francisco J Et Al
Название: Nonparametric Statistical Methods And Related Topics: A Festschrift In Honor Of Professor P K Bhattacharya On The Occasion Of His 80Th Birthday
ISBN: 9814366560 ISBN-13(EAN): 9789814366564
Издательство: World Scientific Publishing
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Цена: 158400.00 T
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Описание: Consists of 22 research papers in Probability and Statistics. This title includes topics such as nonparametric inference, nonparametric curve fitting, linear model theory, Bayesian nonparametrics, change point problems, time series analysis and asymptotic theory. It presents research in statistical theory.

Автор: Klaus Nordhausen; Sara Taskinen
Название: Modern Nonparametric, Robust and Multivariate Methods
ISBN: 3319361295 ISBN-13(EAN): 9783319361291
Издательство: Springer
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Цена: 102480.00 T
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Описание: Written by leading experts in the field, this edited volume brings together the latest findings in the area of nonparametric, robust and multivariate statistical methods. The individual contributions cover a wide variety of topics ranging from univariate nonparametric methods to robust methods for complex data structures.

Автор: Cinzia Daraio; L?opold Simar
Название: Advanced Robust and Nonparametric Methods in Efficiency Analysis
ISBN: 1441941975 ISBN-13(EAN): 9781441941978
Издательство: Springer
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Цена: 158380.00 T
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Описание:

Providing a systematic and comprehensive treatment of recent developments in efficiency analysis, this readable book makes available an intuitive yet rigorous presentation of advanced nonparametric and robust methods. This flexible toolbox can be used in theories based on the neoclassical theory of production and its alternatives, including evolutionary theories. The methods are complemented by empirical analysis of three different economic fields: scientific research, mutual funds industry and the insurance sector. The research demonstrates the utility of the toolbox for a wide range of economic issues, including the analysis of economies of scale and scope, dynamics of age and agglomeration effects, trade-offs in production and service activities, and explanations of efficiency differentials. Of interest to applied economists broadly, this book will also be of interest to those focused on Operations Research and/or Management Science.

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: 102480.00 T
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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.

Автор: Dieter Rasch; Moti Lal Tiku
Название: Robustness of Statistical Methods and Nonparametric Statistics
ISBN: 9400965303 ISBN-13(EAN): 9789400965300
Издательство: Springer
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Цена: 74490.00 T
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