Discarding Variables in a Principal Component Analysis. Ii: Real Data
Discarding Variables in a Principal Component Analysis. Ii: Real Data
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DOI：
10.2307/2346300
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发表时间：
1973-03
影响因子：
1.6
通讯作者：
I. Jolliffe
中科院分区：
文献类型：
--
作者：
I. Jolliffe
在本文中，它示出了四组真实的数据，所有公布的主成分分析的例子，所使用的变量的数量可以大大减少，得到的结果几乎没有影响。五种方法丢弃变量，这是以前成功地测试人工数据（Jolliffe，1972年），使用。的方法进行比较，所有被证明是令人满意的真实的，以及人工，数据，虽然没有被证明是压倒性的上级的人。
In this paper it is shown for four sets of real data, all published examples of principal component analysis, that the number of variables used can be greatly reduced with little effect on the results obtained. Five methods for discarding variables, which have previously been successfully tested on artificial data (Jolliffe, 1972), are used. The methods are compared and all are shown to be satisfactory for real, as well as artificial, data, although none is shown to be overwhelmingly superior to the others.