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Titlebook: Nonlinear Dynamics in Economics; A Theoretical and St Bärbel Finkenstädt Book 1995 Springer-Verlag Berlin Heidelberg 1995 Fitting.Nichtline

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发表于 2025-3-21 19:23:45 | 显示全部楼层 |阅读模式
书目名称Nonlinear Dynamics in Economics
副标题A Theoretical and St
编辑Bärbel Finkenstädt
视频video
丛书名称Lecture Notes in Economics and Mathematical Systems
图书封面Titlebook: Nonlinear Dynamics in Economics; A Theoretical and St Bärbel Finkenstädt Book 1995 Springer-Verlag Berlin Heidelberg 1995 Fitting.Nichtline
描述1. 1 Introduction In economics, one often observes time series that exhibit different patterns of qualitative behavior, both regular and irregular, symmetric and asymmetric. There exist two different perspectives to explain this kind of behavior within the framework of a dynamical model. The traditional belief is that the time evolution of the series can be explained by a linear dynamic model that is exogenously disturbed by a stochastic process. In that case, the observed irregular behavior is explained by the influence of external random shocks which do not necessarily have an economic reason. A more recent theory has evolved in economics that attributes the patterns of change in economic time series to an underlying nonlinear structure, which means that fluctua­ tions can as well be caused endogenously by the influence of market forces, preference relations, or technological progress. One of the main reasons why nonlinear dynamic models are so interesting to economists is that they are able to produce a great variety of possible dynamic outcomes - from regular predictable behavior to the most complex irregular behavior - rich enough to meet the economists‘ objectives of modeling
出版日期Book 1995
关键词Fitting; Nichtlineare Abhängigkeit; Nonlinear Dynamics; STATISTICA; Time series; Zeitreihen; correlation; p
版次1
doihttps://doi.org/10.1007/978-3-642-46821-6
isbn_softcover978-3-540-59374-4
isbn_ebook978-3-642-46821-6Series ISSN 0075-8442 Series E-ISSN 2196-9957
issn_series 0075-8442
copyrightSpringer-Verlag Berlin Heidelberg 1995
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A Nearest Neighbor Approach to Forecast Nonlinear Time Series,idorowich [1987], to improve the short term prediction of nonlinear chaotic processes. The idea underlying their forecasting algorithm is as follows: For a nonlinear low-dimensional process, a state space reconstruction of the observed time series exhibits “spatial” correlation, which can be exploit
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Conclusions and Outlook,s are a priori linear in nature — provides a real enrichment of what simple dynamical systems in economics can explain. A model which exhibits simple regular behavior in its linear version may perform completely different if it is reformulated to include nonlinearities.
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Book 1995 One of the main reasons why nonlinear dynamic models are so interesting to economists is that they are able to produce a great variety of possible dynamic outcomes - from regular predictable behavior to the most complex irregular behavior - rich enough to meet the economists‘ objectives of modeling
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0075-8442 ossible dynamic outcomes - from regular predictable behavior to the most complex irregular behavior - rich enough to meet the economists‘ objectives of modeling978-3-540-59374-4978-3-642-46821-6Series ISSN 0075-8442 Series E-ISSN 2196-9957
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A Nearest Neighbor Approach to Forecast Nonlinear Time Series, test to accompany the algorithm is suggested here. To demonstrate its practical use, the methodology is applied to the observed agricultural price series. It is found that the short term predictability of the best fitting linear model can be improved upon significantly by this method.
发表于 2025-3-23 06:46:33 | 显示全部楼层
Book 1995mmetric and asymmetric. There exist two different perspectives to explain this kind of behavior within the framework of a dynamical model. The traditional belief is that the time evolution of the series can be explained by a linear dynamic model that is exogenously disturbed by a stochastic process.
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