Derives asymptotic normality of hybrid PCA leading eigenvector estimator in allometric regression and proposes geometric test for direction parallelism avoiding minor-eigenvalue instability; applied to painted turtle data confirming prior allometric findings.
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Hybrid principal component analysis in multivariate allometric regression
Derives asymptotic normality of hybrid PCA leading eigenvector estimator in allometric regression and proposes geometric test for direction parallelism avoiding minor-eigenvalue instability; applied to painted turtle data confirming prior allometric findings.