A Combined Parametric And Nonparametric Approach To Time Series Analysis
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A Combined Parametric And Nonparametric Approach To Time Series Analysis
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Author : Stefan Kriebol
language : en
Publisher: IOS Press
Release Date : 1999
A Combined Parametric And Nonparametric Approach To Time Series Analysis written by Stefan Kriebol and has been published by IOS Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1999 with Mathematics categories.
The analysis and prediction of natural phenomena is an interesting and challenging task. Time series obtained from the observation of one or more features of a phenomenon are often the only access to the data generating system. Unfortunately, time series analysis is usually done by specialists in the field of the phenomenon with traditional analysis techniques. The application of modern analysis and prediction tools is often avoided due to their complexity or the risk of failure. This issue can be surmounted by an interdisciplinary approach. This work is an example for the possible synergetic effect of interdisciplinary research. In the field of oceanography the coastal upwelling phenomenon is analysed in experimental studies with a numerical model in order to develop a parametric prediction model. Artificial neural networks seem to be a suitable parametric model. However, in the field of computer science traditional artificial neural techniques showed limitations in the analysis and prediction of time series obtained from natural phenomena, particularly with nonlinear and nonstationary time series. Motivated by this limitations a new approach to time series analysis and prediction is presented in this work, the mixture of nonparametric segmented experts (MONSE). The MONSE approach is exploiting the synergetic effect of a combined nonparametric and parametric analysis. It is supposed to be applied to explorative time series analysis and prediction in various fields, i.e. in a context where hardly any kowledge about the time series of concern is available.
Nonlinear Time Series
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Author : Jianqing Fan
language : en
Publisher: Springer Science & Business Media
Release Date : 2008-09-11
Nonlinear Time Series written by Jianqing Fan 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 2008-09-11 with Mathematics categories.
This is the first book that integrates useful parametric and nonparametric techniques with time series modeling and prediction, the two important goals of time series analysis. Such a book will benefit researchers and practitioners in various fields such as econometricians, meteorologists, biologists, among others who wish to learn useful time series methods within a short period of time. The book also intends to serve as a reference or text book for graduate students in statistics and econometrics.
Time Series Analysis
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Author : Rifaat Abdalla
language : en
Publisher: BoD – Books on Demand
Release Date : 2023-01-18
Time Series Analysis written by Rifaat Abdalla and has been published by BoD – Books on Demand this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-01-18 with Computers categories.
Time series data consist of a collection of observations obtained through repeated measurements over time. When the points are plotted on a graph, one of the axes is always time. Time series analysis is a specific way of analyzing a sequence of data points. Time series data are everywhere since time is a constituent of everything that is observable. As our world becomes increasingly digitized, sensors and systems are constantly emitting a relentless stream of time series data, which has numerous applications across various industries. The editors of this book are happy to provide the specialized reader community with this book as a modest contribution to this rapidly developing domain.
New Directions In Time Series Analysis
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Author : David Brillinger
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06
New Directions In Time Series Analysis written by David Brillinger 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 NEW DIRECTIONS IN TIME SERIES ANALYSIS, PART II is based on the proceedings of the IMA summer program "New Directions in Time Series Analysis. " We are grateful to David Brillinger, Peter Caines, John Geweke, Emanuel Parzen, Murray Rosenblatt, and Murad Taqqu for organizing the program and we hope that the remarkable excitement and enthusiasm of the participants in this interdisciplinary effort are communicated to the reader. A vner Friedman Willard Miller, Jr. PREFACE Time Series Analysis is truly an interdisciplinary field because development of its theory and methods requires interaction between the diverse disciplines in which it is applied. To harness its great potential, strong interaction must be encouraged among the diverse community of statisticians and other scientists whose research involves the analysis of time series data. This was the goal of the IMA Workshop on "New Directions in Time Series Analysis. " The workshop was held July 2-July 27, 1990 and was organized by a committee consisting of Emanuel Parzen (chair), David Brillinger, Murray Rosenblatt, Murad S. Taqqu, John Geweke, and Peter Caines. Constant guidance and encouragement was provided by Avner Friedman, Director of the IMA, and his very helpful and efficient staff. The workshops were organized by weeks. It may be of interest to record the themes that were announced in the IMA newsletter describing the workshop: l.
Learning Search Control Knowledge For Equational Deduction
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Author : S. A. Schulz
language : en
Publisher: IOS Press
Release Date : 2000
Learning Search Control Knowledge For Equational Deduction written by S. A. Schulz and has been published by IOS Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2000 with Computers categories.
This thesis presents an approach to learning good search guiding heuristics for the supposition-based theorom prover E in equational deductions. Search decisions from successful proof searches are represented as sets annotated clause patterns. Term Space Mapping, an alternative learning method for recursive structures is used to learn heuristic evaluation functions for the evaluation of potential new consequences. Experimental results with extended system E/TSM show the success of the approach. Additional contributions of the thesis are an extended superposition calculus and a description of both the proof procedure and the implementation of a state-of-the-art equational theorem prover.
Scenario Analysis In Risk Management
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Author : Bertrand K. Hassani
language : en
Publisher: Springer
Release Date : 2016-10-26
Scenario Analysis In Risk Management written by Bertrand K. Hassani and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-10-26 with Business & Economics categories.
This book focuses on identifying and explaining the key determinants of scenario analysis in the context of operational risk, stress testing and systemic risk, as well as management and planning. Each chapter presents alternative solutions to perform reliable scenario analysis. The author also provides technical notes and describes applications and key characteristics for each of the solutions. In addition, the book includes a section to help practitioners interpret the results and adjust them to real-life management activities. Methodologies, including those derived from consensus strategies, extreme value theory, Bayesian networks, Neural networks, Fault Trees, frequentist statistics and data mining are introduced in such a way as to make them understandable to readers without a quantitative background. Particular emphasis is given to the added value of the implementation of these methodologies.
Nonlinear Time Series Analysis
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Author : Ruey S. Tsay
language : en
Publisher: John Wiley & Sons
Release Date : 2018-09-13
Nonlinear Time Series Analysis written by Ruey S. Tsay 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 2018-09-13 with Mathematics categories.
A comprehensive resource that draws a balance between theory and applications of nonlinear time series analysis Nonlinear Time Series Analysis offers an important guide to both parametric and nonparametric methods, nonlinear state-space models, and Bayesian as well as classical approaches to nonlinear time series analysis. The authors—noted experts in the field—explore the advantages and limitations of the nonlinear models and methods and review the improvements upon linear time series models. The need for this book is based on the recent developments in nonlinear time series analysis, statistical learning, dynamic systems and advanced computational methods. Parametric and nonparametric methods and nonlinear and non-Gaussian state space models provide a much wider range of tools for time series analysis. In addition, advances in computing and data collection have made available large data sets and high-frequency data. These new data make it not only feasible, but also necessary to take into consideration the nonlinearity embedded in most real-world time series. This vital guide: • Offers research developed by leading scholars of time series analysis • Presents R commands making it possible to reproduce all the analyses included in the text • Contains real-world examples throughout the book • Recommends exercises to test understanding of material presented • Includes an instructor solutions manual and companion website Written for students, researchers, and practitioners who are interested in exploring nonlinearity in time series, Nonlinear Time Series Analysis offers a comprehensive text that explores the advantages and limitations of the nonlinear models and methods and demonstrates the improvements upon linear time series models.
Action Based Collaboration Analysis For Group Learning
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Author : Martin Mühlenbrock
language : en
Publisher: IOS Press
Release Date : 2001
Action Based Collaboration Analysis For Group Learning written by Martin Mühlenbrock and has been published by IOS Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2001 with Computers categories.
Shared-workspace systems with structured graphical representations allow for the free user interaction and the joint construction of problem solutions for potentially open-ended tasks. However, group modelling in shared workspaces has to take on a process-orientated perspective due to the reduced system control in shared workspaces. This text is defined as the monitoring of user actions and the abstraction and interpretation of the raw data in the context of the group interaction and the problem representation. Formally based on plan recognition and the situation calculus, an approach has been developed that incorporates an operational hierarchy for generally modelling activities. The system performs an automatic inline analysis of group interactions and the results are visualized in different forms to give feedback and stimulating self-reflection.
Connection Tableau Calculi With Disjunctive Constraints
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Author : Ortrun Ibens
language : en
Publisher: IOS Press
Release Date : 1999
Connection Tableau Calculi With Disjunctive Constraints written by Ortrun Ibens and has been published by IOS Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1999 with Computers categories.
Automated deduction is one of the fundamental disciplines in the field of artificial intelligence. The purpose of systems for automated deduction is to find formal proofs for given conjectures by drawing conclusions from formally specified knowledge. Their main strength is that they allow a purely declarative description of knowledge, i.e., procedural information on the drawing of conclusions need not be provided. In combination with the indeterminism in the drawing of possible conclusions, however, the ability to handle declarative specifications introduces the aspect of search into the deduction process. Usually, tremendous search spaces have to be explored in order to find a proof. Successful systems for automated deduction can be built, for example, on the basis of connection tableau calculi. In this thesis, an approach to a more intelligent search in connection tableau calculi is made. The approach is based on the compression of structurally similar formulas given to and derived by connection tableau calculi. Disjunctive constraints over first order terms are used to express the results of the compression. There are two main theoretical results of the thesis. Firstly, it introduces a new class of sound and complete connection tableau calculi, the so-called constrained-connection-tableau calculi, which are compatible with the most important search pruning techniques of conventional connection tableau calculi. Secondly, intelligent algorithms for solving disjunctive constraints over first order terms are developed. As a practical result, the implementation of the approach leads to a powerful system for automated deduction which demonstrates the high potential of the new developments.
Handbook Of Mixed Membership Models And Their Applications
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Author : Edoardo M. Airoldi
language : en
Publisher: CRC Press
Release Date : 2014-11-06
Handbook Of Mixed Membership Models And Their Applications written by Edoardo M. Airoldi and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-11-06 with Computers categories.
In response to scientific needs for more diverse and structured explanations of statistical data, researchers have discovered how to model individual data points as belonging to multiple groups. Handbook of Mixed Membership Models and Their Applications shows you how to use these flexible modeling tools to uncover hidden patterns in modern high-dimensional multivariate data. It explores the use of the models in various application settings, including survey data, population genetics, text analysis, image processing and annotation, and molecular biology. Through examples using real data sets, you’ll discover how to characterize complex multivariate data in: Studies involving genetic databases Patterns in the progression of diseases and disabilities Combinations of topics covered by text documents Political ideology or electorate voting patterns Heterogeneous relationships in networks, and much more The handbook spans more than 20 years of the editors’ and contributors’ statistical work in the field. Top researchers compare partial and mixed membership models, explain how to interpret mixed membership, delve into factor analysis, and describe nonparametric mixed membership models. They also present extensions of the mixed membership model for text analysis, sequence and rank data, and network data as well as semi-supervised mixed membership models.