Models with commutative orthogonal block structure: a general condition for commutativity. Issue 13 (17th November 2020)

• Record Type: Journal Article
• Authors: Santos, C.; Nunes, C.; Dias, C.; Mexia, J.T.
• Is Part Of: Journal of applied statistics. Volume 47:Issue 13/15(2020)
• Page Start: 2421
• Page End: 2430
• Publication Date: 2020-11-17
• Subjects: U-matrices -- best linear unbiased estimators -- mixed models -- models with commutative orthogonal block structure; Statistics -- Periodicals; 519.5
• DOI: 10.1080/02664763.2020.1765322
• Languages: English
• ISSNs: 0266-4763

Abstract

Abstract : A linear mixed model whose variance-covariance matrix is a linear combination of known pairwise orthogonal projection matrices that add to the identity matrix, is a model with orthogonal block structure (OBS). OBS have estimators with good behavior for estimable vectors and variance components, moreover it may be interesting that the least squares estimators give the best linear unbiased estimators, for estimable vectors. We can achieve it, requiring commutativity between the orthogonal projection matrix, on the space spanned by the mean vector, and the orthogonal projection matrices involved in the expression of the variance-covariance matrix. This commutativity condition defines a more restrict class of OBS, named COBS (model with commutative orthogonal block structure). With this work we aim to present a commutativity condition, resorting to a special class of matrices, named U-matrices.