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Neural Networks Applications in Economics: a Statistical Point of View

机译:神经网络在经济学中的应用:统计观点

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Nowdays neural networks (NN) are applied in the most various fields and are actually receiving a lot of attention among the researcher's community. In this paper we will provide a review of some NN applictions in economics. We distinguish the applications according to the main objectives achieved by NN in this field: prediction, classification and modeling economic theory. It is a matte of fact that NN share with statistics a lot of methodological and computational aspects as well as many fields of application. In this framework we introduce a general strategy for a statistical approach to NN which allows to use NN in a statistical context taking into account typical statistical applications problems, such as the slection and coding of the variables, the sample representativeness but more the interpretation, visualization and stability of the results.
机译:现在,目前的神经网络(NN)适用于最多的领域,实际上在研究人员的社区中受到了很多关注。在本文中,我们将对经济学中的一些NN施加进行审查。我们根据本领域NN实现的主要目标区分应用程序:预测,分类和经济理论。这是一个事实,即NN与统计数据很多方法学和计算方面以及许多应用领域。在本框架中,我们向NN介绍一个统计方法的一般策略,它允许在统计上下文中使用NN,以考虑典型的统计应用问题,例如变量的插页和编码,样本代表性,但更多的解释,可视化和结果的稳定性。

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