Main Article Content
Abstract
Young, Scariano, and Hallum (2005) study two univariate linear regression models, and establish a certain condition for the variances estimates to be equal; however, the condition is in error. They then apply this incorrect condition to some unknown completely randomized design model. The present paper records the correct condition for the equality of the context variances, and points out that this condition cannot be applied to experimental design models.
Keywords
equality of regression parametric estimates
equality of the covariances
Randomized Blocks design
full rank generalized inverse
generalized inverse
Moore-Penrose inverse
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How to Cite
Gupta, A. K., & Kabe, D. G. (2011). Covariance Structures of Linear Models. Pakistan Journal of Statistics and Operation Research, 7(2-Sp). https://doi.org/10.18187/pjsor.v7i2-Sp.298
