2001•BiometrikaRequires access

Conditional test for rank in bivariate canonical correlation analysis

Bent Juhl Nielsen

Open publisher page 8 citations

Abstract

The likelihood ratio test for the hypothesis that the smaller of two canonical correlations is zero is nonsimilar; the distribution of the test statistic depends on the value of the largest canonical correlation. In applications the nuisance parameter usually has to be estimated, and this paper describes the distributional properties of the test, conditional on the estimator. Although these properties depend on the nuisance parameter, the dependency seems to be negligible for practical purposes.

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What this paper is about

The likelihood ratio test for the hypothesis that the smaller of two canonical correlations is zero is nonsimilar; the distribution of the test statistic depends on the value of the largest canonical correlation. In applications the nuisance parameter usually has to be estimated, and this paper describes the distributional properties of the test, conditional on the estimator. Although these properties depend on the nuisance parameter, the dependency seems to be negligible for practical purposes.

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OpenAlex reports 8 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

The likelihood ratio test for the hypothesis that the smaller of two canonical correlations is zero is nonsimilar; the distribution of the test statistic depends on the value of the largest canonical correlation. In applications the nuisance parameter usually has to be estimated, and this paper describes the distributional properties of the test, conditional on the estimator. Although these properties depend on the nuisance parameter, the dependency seems to be negligible for practical purposes.

Key concepts: Mathematics, Canonical correlation, Bivariate analysis, Statistics, Canonical analysis, Nuisance parameter, Test statistic, Dependency (UML)

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