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Robust And Nonlinear Time Series Analysis


Robust And Nonlinear Time Series Analysis
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Robust And Nonlinear Time Series Analysis


Robust And Nonlinear Time Series Analysis
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Author : J. Franke
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06

Robust And Nonlinear Time Series Analysis written by J. Franke and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Mathematics categories.


Classical time series methods are based on the assumption that a particular stochastic process model generates the observed data. The, most commonly used assumption is that the data is a realization of a stationary Gaussian process. However, since the Gaussian assumption is a fairly stringent one, this assumption is frequently replaced by the weaker assumption that the process is wide~sense stationary and that only the mean and covariance sequence is specified. This approach of specifying the probabilistic behavior only up to "second order" has of course been extremely popular from a theoretical point of view be cause it has allowed one to treat a large variety of problems, such as prediction, filtering and smoothing, using the geometry of Hilbert spaces. While the literature abounds with a variety of optimal estimation results based on either the Gaussian assumption or the specification of second-order properties, time series workers have not always believed in the literal truth of either the Gaussian or second-order specifica tion. They have none-the-less stressed the importance of such optimali ty results, probably for two main reasons: First, the results come from a rich and very workable theory. Second, the researchers often relied on a vague belief in a kind of continuity principle according to which the results of time series inference would change only a small amount if the actual model deviated only a small amount from the assum ed model.



Nonlinear Time Series Analysis In The Geosciences


Nonlinear Time Series Analysis In The Geosciences
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Author : Reik V. Donner
language : en
Publisher: Springer Science & Business Media
Release Date : 2008-08-18

Nonlinear Time Series Analysis In The Geosciences written by Reik V. Donner and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-08-18 with Mathematics categories.


The understanding of dynamical processes in the complex system “Earth” requires the appropriate analysis of a large amount of data from observations and/or model simulations. In this volume, modern nonlinear approaches are introduced and used to study specifiic questions relevant to present-day geoscience. The approaches include spatio-temporal methods, time-frequency analysis, dimension analysis (in particular, for multivariate data), nonlinear statistical decomposition, methods designed for treating data with uneven sampling or missing values, nonlinear correlation and synchronization analysis, surrogate data techniques, network approaches, and nonlinear methods of noise reduction. This book aims to present a collection of state-of-the-art scientific contributions used in current studies by some of the world's leading scientists in this field.



Elements Of Nonlinear Time Series Analysis And Forecasting


Elements Of Nonlinear Time Series Analysis And Forecasting
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Author : Jan G. De Gooijer
language : en
Publisher: Springer
Release Date : 2017-03-30

Elements Of Nonlinear Time Series Analysis And Forecasting written by Jan G. De Gooijer and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-03-30 with Mathematics categories.


This book provides an overview of the current state-of-the-art of nonlinear time series analysis, richly illustrated with examples, pseudocode algorithms and real-world applications. Avoiding a “theorem-proof” format, it shows concrete applications on a variety of empirical time series. The book can be used in graduate courses in nonlinear time series and at the same time also includes interesting material for more advanced readers. Though it is largely self-contained, readers require an understanding of basic linear time series concepts, Markov chains and Monte Carlo simulation methods. The book covers time-domain and frequency-domain methods for the analysis of both univariate and multivariate (vector) time series. It makes a clear distinction between parametric models on the one hand, and semi- and nonparametric models/methods on the other. This offers the reader the option of concentrating exclusively on one of these nonlinear time series analysis methods. To make the book as user friendly as possible, major supporting concepts and specialized tables are appended at the end of every chapter. In addition, each chapter concludes with a set of key terms and concepts, as well as a summary of the main findings. Lastly, the book offers numerous theoretical and empirical exercises, with answers provided by the author in an extensive solutions manual.



Nonlinear Time Series Analysis Of Economic And Financial Data


Nonlinear Time Series Analysis Of Economic And Financial Data
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Author : Philip Rothman
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06

Nonlinear Time Series Analysis Of Economic And Financial Data written by Philip Rothman and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Business & Economics categories.


Nonlinear Time Series Analysis of Economic and Financial Data provides an examination of the flourishing interest that has developed in this area over the past decade. The constant theme throughout this work is that standard linear time series tools leave unexamined and unexploited economically significant features in frequently used data sets. The book comprises original contributions written by specialists in the field, and offers a combination of both applied and methodological papers. It will be useful to both seasoned veterans of nonlinear time series analysis and those searching for an informative panoramic look at front-line developments in the area.



Directions In Robust Statistics And Diagnostics


Directions In Robust Statistics And Diagnostics
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Author : Werner Stahel
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06

Directions In Robust Statistics And Diagnostics written by Werner Stahel and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Mathematics categories.


This IMA Volume in Mathematics and its Applications DIRECTIONS IN ROBUST STATISTICS AND DIAGNOSTICS is based on the proceedings of the first four weeks of the six week IMA 1989 summer program "Robustness, Diagnostics, Computing and Graphics in Statistics". An important objective of the organizers was to draw a broad set of statisticians working in robustness or diagnostics into collaboration on the challenging problems in these areas, particularly on the interface between them. We thank the organizers of the robustness and diagnostics program Noel Cressie, Thomas P. Hettmansperger, Peter J. Huber, R. Douglas Martin, and especially Werner Stahel and Sanford Weisberg who edited the proceedings. A vner Friedman Willard Miller, Jr. PREFACE Central themes of all statistics are estimation, prediction, and making decisions under uncertainty. A standard approach to these goals is through parametric mod elling. Parametric models can give a problem sufficient structure to allow standard, well understood paradigms to be applied to make the required inferences. If, how ever, the parametric model is not completely correct, then the standard inferential methods may not give reasonable answers. In the last quarter century, particularly with the advent of readily available computing, more attention has been paid to the problem of inference when the parametric model used is not correctly specified.



Statistics Of Financial Markets


Statistics Of Financial Markets
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Author : Jürgen Franke
language : en
Publisher: Springer
Release Date : 2019-06-11

Statistics Of Financial Markets written by Jürgen Franke and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-06-11 with Business & Economics categories.


Now in its fifth edition, this book offers a detailed yet concise introduction to the growing field of statistical applications in finance. The reader will learn the basic methods for evaluating option contracts, analyzing financial time series, selecting portfolios and managing risks based on realistic assumptions about market behavior. The focus is both on the fundamentals of mathematical finance and financial time series analysis, and on applications to specific problems concerning financial markets, thus making the book the ideal basis for lectures, seminars and crash courses on the topic. All numerical calculations are transparent and reproducible using quantlets. For this new edition the book has been updated and extensively revised and now includes several new aspects such as neural networks, deep learning, and crypto-currencies. Both R and Matlab code, together with the data, can be downloaded from the book’s product page and the Quantlet platform. The Quantlet platform quantlet.de, quantlet.com, quantlet.org is an integrated QuantNet environment consisting of different types of statistics-related documents and program codes. Its goal is to promote reproducibility and offer a platform for sharing validated knowledge native to the social web. QuantNet and the corresponding Data-Driven Documents-based visualization allow readers to reproduce the tables, pictures and calculations inside this Springer book. “This book provides an excellent introduction to the tools from probability and statistics necessary to analyze financial data. Clearly written and accessible, it will be very useful to students and practitioners alike.” Yacine Ait-Sahalia, Otto Hack 1903 Professor of Finance and Economics, Princeton University



Statistical Data Analysis Based On The L1 Norm And Related Methods


Statistical Data Analysis Based On The L1 Norm And Related Methods
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Author : Yadolah Dodge
language : en
Publisher: Birkhäuser
Release Date : 2012-12-06

Statistical Data Analysis Based On The L1 Norm And Related Methods written by Yadolah Dodge and has been published by Birkhäuser this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Mathematics categories.


This volume contains a selection of invited papers, presented to the fourth In Statistical Analysis Based on the L1-Norm and Related ternational Conference on Methods, held in Neuchatel, Switzerland, from August 4-9, 2002. Organized jointly by the University of Illinois at Chicago (Gib Bassett), the Rutgers University (Regina Liu and Yehuda Vardi) and the University of Neuchatel (Yadolah Dodge), the conference brought together experts whose research deals with theory and ap plications involving the L1-Norm. The conference included invited and contributed talks as well as a tutorial on Quantile Regression. This volume includes 36 refereed invited papers under seven headings. Part one deals with Quantiles in all their forms and shapes. It includes papers on quantile functions in non-parametric multivariate analysis, and empirical applications of quantile regression. Much of the development in this direction follows from the fundamental paper by Koenker and Bassett in 1978. Financial and Time Series A nalysis follows the section on quantiles. Part three concerns Estimation, Testing and Characterization. Part four, Deep in the Data, deals with issues related to data depth. Part five addresses Classification questions. The problem of Density Estimation and Image Processing is discussed in Part six, and finally Part seven presents two environmental applications. The contributions represent clear evidence of important research involving theo retical issues and applications associated with the L1-Norm. It is my hope that the articles contained in this volume and its predecessors, published in 1987, 1992, and 1997, will stimulate interest among researchers.



Six Sigma For Organizational Excellence


Six Sigma For Organizational Excellence
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Author : K. Muralidharan
language : en
Publisher: Springer
Release Date : 2015-04-22

Six Sigma For Organizational Excellence written by K. Muralidharan and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-04-22 with Mathematics categories.


This book discusses the integrated concepts of statistical quality engineering and management tools. It will help readers to understand and apply the concepts of quality through project management and technical analysis, using statistical methods. Prepared in a ready-to-use form, the text will equip practitioners to implement the Six Sigma principles in projects. The concepts discussed are all critically assessed and explained, allowing them to be practically applied in managerial decision-making, and in each chapter, the objectives and connections to the rest of the work are clearly illustrated. To aid in understanding, the book includes a wealth of tables, graphs, descriptions and checklists, as well as charts and plots, worked-out examples and exercises. Perhaps the most unique feature of the book is its approach, using statistical tools, to explain the science behind Six Sigma project management and integrated in engineering concepts. The material on quality engineering and statistical management tools offers valuable support for undergraduate, postgraduate and research students. The book can also serve as a concise guide for Six Sigma professionals, Green Belt, Black Belt and Master Black Belt trainers.



Groundwater Contamination Use Of Models In Decision Making


Groundwater Contamination Use Of Models In Decision Making
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Author : G. Jousma
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06

Groundwater Contamination Use Of Models In Decision Making written by G. Jousma and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Science categories.


The protection of groundwater resources has emerged in recent years as a high priority topic on the agenda of many countries. In responding to the growing concern over deteriorating groundwater quality, many countries are developing a comprehensive regulatory framework for the management of subsurface water resources with management referring to both quantity and quality aspects. Within this framework, groundwater models are rapidly coming to playa central role in the development of protection and rehabilitation strategies. These models provide forecasts of the future state of the groundwater aquifer systems and/or the unsaturated zone in response to proposed management initiatives. For example, models will predict the effects of implementing a proposed management scheme on water levels and on the transport and fate of pollutants. The models are now used in the formulation of policies and regulations, the issuing of permits, design of monitoring and data collection systems, and the development of enforcement actions. The growth in the use of these sophisticated tools has led to many unforeseen problems in groundwater management. Lingering issues include reliability of codes, quality assurance in model development and applications, efficient utiliza tion of human and material resources, technology transfer and training. Some issues have legal ramifications, as in cases where the applications of models have been contested in courts.



Robustness Theory And Application


Robustness Theory And Application
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Author : Brenton R. Clarke
language : en
Publisher: John Wiley & Sons
Release Date : 2018-06-21

Robustness Theory And Application written by Brenton R. Clarke and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-06-21 with Mathematics categories.


A preeminent expert in the field explores new and exciting methodologies in the ever-growing field of robust statistics Used to develop data analytical methods, which are resistant to outlying observations in the data, while capable of detecting outliers, robust statistics is extremely useful for solving an array of common problems, such as estimating location, scale, and regression parameters. Written by an internationally recognized expert in the field of robust statistics, this book addresses a range of well-established techniques while exploring, in depth, new and exciting methodologies. Local robustness and global robustness are discussed, and problems of non-identifiability and adaptive estimation are considered. Rather than attempt an exhaustive investigation of robustness, the author provides readers with a timely review of many of the most important problems in statistical inference involving robust estimation, along with a brief look at confidence intervals for location. Throughout, the author meticulously links research in maximum likelihood estimation with the more general M-estimation methodology. Specific applications and R and some MATLAB subroutines with accompanying data sets—available both in the text and online—are employed wherever appropriate. Providing invaluable insights and guidance, Robustness Theory and Application: Offers a balanced presentation of theory and applications within each topic-specific discussion Features solved examples throughout which help clarify complex and/or difficult concepts Meticulously links research in maximum likelihood type estimation with the more general M-estimation methodology Delves into new methodologies which have been developed over the past decade without stinting on coverage of “tried-and-true” methodologies Includes R and some MATLAB subroutines with accompanying data sets, which help illustrate the power of the methods described Robustness Theory and Application is an important resource for all statisticians interested in the topic of robust statistics. This book encompasses both past and present research, making it a valuable supplemental text for graduate-level courses in robustness.