Abstract
In order to reproduce the evolution of real economy over long period, a global model may be attempted to give a description of the dynamics with a small set of model coefficients. Then, the problem is to obtain a global model which is able to reproduce all the dynamical behavior of the data set studied starting from a set of initial conditions. Such a global model may be built on derivatives coordinates, i.e. the recorded time series and its successive derivatives. In this chapter, the mathematical background of a gobal modeling technique based on such a differential embedding will be exemplified on test cases of the real world (electrochemical and chemical experiments). Difficulties encountered in global modeling related to the nature of economic data records will be discussed. Properties of the time series required for a successful differential model will be defined.
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Maquet, J., Letellier, C., Gouesbet, G. (2002). Global Modeling and Differential Embedding. In: Soofi, A.S., Cao, L. (eds) Modelling and Forecasting Financial Data. Studies in Computational Finance, vol 2. Springer, Boston, MA. https://doi.org/10.1007/978-1-4615-0931-8_17
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DOI: https://doi.org/10.1007/978-1-4615-0931-8_17
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