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摘要
En 中文
A new multivariate statistical technique is obtained for comparing and combining two or more data sets each of which has a different number of respondents but the same variables. This approach can be considered as dual to such techniques as partial least squares, also known as inter-battery factor analysis and robust canonical correlation analysis for two data sets. It is shown that the problem can be reduced to the eigenproblem of the product of correlation matrices of each data set. The technique is generalized to three or more data sets in an eigenproblem of block-matrices of the correlations within each data set. This type of multivariate analysis can serve various practical problems of integration of data obtained from heterogeneous sources, particularly, for data merging in constructing data warehouses.
Keyword:
Dual multivariate statistical analysis
partial least squares
inter-battery factor analysis
robust canonical correlations
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I
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1.8
论文数:
5
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1.4K
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