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Sensitivity analysis in multivariate methods: Decomposition of an arbitrary influence into a finite number of components |
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| Authors: | Yutaka Tanaka Eduardo Tostado Castaño |
| Institution: | 1. Department of Statistics , Okayama University , Tsushima, Okayama, 700, Japan;2. Graduate School of Natural Science and Technology , Okayama University , Tsushima, Okayama, 700, Japan |
| Abstract: | The influence function of the covariance matrix is decomposed into a finite number of components. This decomposition provides a useful tool to develop efficient methods for computing empirical influence curves related to various multivariate methods. It can also be used to characterize multivariate methods from the sensitivity perspective. A numerical example is given to demonstrate efficient computing and to characterize some procedures of exploratory factor analysis. |
| Keywords: | sensitivity analysis influence function principal component analysis canonical correlation analysis factor analysis efficient computing characterization of multivariate methods |