Doubly multivariate linear models with block exchangeable distributed errors and site-dependent covariates

ABSTRACT

The problem of testing the intercept and slope parameters of doubly multivariate linear models with site-dependent covariates using Rao's score test (RST) is studied. The RST statistic is developed for a block exchangeable covariance structure on the error vector under the assumption of multivariate normality. We compare our developed RST statistic with the likelihood ratio test (LRT) statistic. Monte Carlo simulations indicate that the RST statistic is much more accurate than its counterpart LRT statistic and it takes significantly less computation time than the LRT statistic. The proposed method is illustrated with an example of multiple response variables measured on multiple trees in a single plot in an agricultural study.

KEYWORDS:

• Block exchangeable covariance structure
• covariance structure models
• hypothesis tests
• Monte Carlo simulations
• Rao's score test

2010 MATHEMATICS SUBJECT CLASSIFICATIONS:

• 62J05
• 62H10
• 62H15

Acknowledgments

The authors want to thank the associate editor and the two anonymous reviewers for their careful reading and valuable suggestions that led to a quite improved version of the manuscript.

Disclosure statement

No potential conflict of interest was reported by the author(s).