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Efficient variable screening for multivariate analysis
被引:26
|作者:
Silva, APD
[1
]
机构:
[1] Univ Catlolica Portuguesa Porto, Porto, Portugal
关键词:
variable selection algorithms;
discriminant analysis;
canonical correlation analysis;
additional information hypothesis;
multivariate indices;
D O I:
10.1006/jmva.2000.1920
中图分类号:
O21 [概率论与数理统计];
C8 [统计学];
学科分类号:
020208 ;
070103 ;
0714 ;
摘要:
It is shown how known algorithms for the comparison of all variables subsets in regression analysis can be adapted to subset comparisons in multivariate analysis, according to any index based on Wilks, Lawley Hotelling, or Bartlet-Pillai statistics and, in some special cases, according to any Function of Ihc sample squared canonical correlations. The issues regarding the choice of an appropriate comparison criterion are discussed. Thc computational effort of the proposed algorithms is studied, and it is argued thai. for a moderate number of variables, they should be preferred to stepwise selection methods. A software implementation of thy methods discussed is Freely available and can be downloaded from the Internet. (C) 2001 Academic Press. AMS 1991 subject classifications: 62H20; 62H30.
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页码:35 / 62
页数:28
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