Clustering techniques for the detection of business cycles

被引：0
|
作者：
Theis, W [1 ]
Weihs, C [1 ]
机构：
[1] Univ Dortmund, SFB 475, D-44221 Dortmund, Germany
来源：
CLASSIFICATION AND INFORMATION PROCESSING AT THE TURN OF THE MILLENNIUM | 2000年
关键词：
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In this paper business cycles are considered as a multivariate phenomenon and not as a univariate one determined e.g. by the GNP. The subject is to look for the number of phases of a business cycle, which can be motivated by the number of clusters in a given dataset of macro-economical variables. Different approaches to distances in the data are tried in a fuzzy cluster analysis to pursue this goal.
引用
收藏
页码：127 / 134
页数：8
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