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Author: Stefan Kriebol
Publisher: IOS Press
ISBN: 9781586031206
Category : Mathematics
Languages : en
Pages : 150
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Book Description
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.
Author: Stefan Kriebol
Publisher: IOS Press
ISBN: 9781586031206
Category : Mathematics
Languages : en
Pages : 150
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Book Description
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.
Author: Stefan K. T. Kriebel
Publisher:
ISBN: 9783896012227
Category : Time series analysis
Languages : en
Pages : 122
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Book Description
Author: Jianqing Fan
Publisher: Springer Science & Business Media
ISBN: 0387693955
Category : Mathematics
Languages : en
Pages : 565
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Book Description
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.
Author: Jiti Gao
Publisher: CRC Press
ISBN: 1420011219
Category : Mathematics
Languages : en
Pages : 249
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Book Description
Useful in the theoretical and empirical analysis of nonlinear time series data, semiparametric methods have received extensive attention in the economics and statistics communities over the past twenty years. Recent studies show that semiparametric methods and models may be applied to solve dimensionality reduction problems arising from using fully
Author: Ayush Kumar
Publisher:
ISBN:
Category :
Languages : en
Pages : 49
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Book Description
Author: Institute of Statistical Mathematics
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Book Description
Author: NERLOVE
Publisher: Birkhäuser
ISBN:
Category : Computers
Languages : en
Pages : 108
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Book Description
The last decade has witnessed an increased interest in time series analysis. Non-parametric methods like spectral and cross spectral analysis are used to discover regularities in individual time series, re lationships between specific components of different time series and leads or lags between those series. Box-Jenkins procedures for the pa rametric estimation of autoregressive-moving average schemes be long nowadays to the standard equipment of a computer center. In economics this revival of time series analysis has led to numer ous empirical studies on optimal seasonal adjustment procedures, the behavior of prices, production, employment etc. More recently, Box Jenkins methods form an integral part for tests on the efficiency of markets, the effectiveness of monetary and fiscal policies and for the study of the röle of different assumptions on the formation of expec tations. This volume comprehends aseries of lectures which deal with var ious topics of time series analysis delivered during the wintersemester 1978/79 at the faculty of economics and statistics. The collection be gins with a paper by M. Nerlove introducing the concept of unob served components. Theoretical results are illustrated by examples se ries on prices of steers, heifers, cows and milk, of cattle and for time hog slaughter, of industrial production and male unemployment. The study by S. Heiler considers a mixed model with a linear regression part and a regular residual process for the prediction of economic processes when additional information is available.
Author: Qi Li
Publisher: Princeton University Press
ISBN: 1400841062
Category : Business & Economics
Languages : en
Pages : 769
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Book Description
A comprehensive, up-to-date textbook on nonparametric methods for students and researchers Until now, students and researchers in nonparametric and semiparametric statistics and econometrics have had to turn to the latest journal articles to keep pace with these emerging methods of economic analysis. Nonparametric Econometrics fills a major gap by gathering together the most up-to-date theory and techniques and presenting them in a remarkably straightforward and accessible format. The empirical tests, data, and exercises included in this textbook help make it the ideal introduction for graduate students and an indispensable resource for researchers. Nonparametric and semiparametric methods have attracted a great deal of attention from statisticians in recent decades. While the majority of existing books on the subject operate from the presumption that the underlying data is strictly continuous in nature, more often than not social scientists deal with categorical data—nominal and ordinal—in applied settings. The conventional nonparametric approach to dealing with the presence of discrete variables is acknowledged to be unsatisfactory. This book is tailored to the needs of applied econometricians and social scientists. Qi Li and Jeffrey Racine emphasize nonparametric techniques suited to the rich array of data types—continuous, nominal, and ordinal—within one coherent framework. They also emphasize the properties of nonparametric estimators in the presence of potentially irrelevant variables. Nonparametric Econometrics covers all the material necessary to understand and apply nonparametric methods for real-world problems.
Author: Rifaat Abdalla
Publisher: BoD – Books on Demand
ISBN: 1803563052
Category : Computers
Languages : en
Pages : 206
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Book Description
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.
Author: Martin Mühlenbrock
Publisher: IOS Press
ISBN: 9781586031756
Category : Computers
Languages : en
Pages : 212
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Book Description
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.
