Mean driven balance and uniformly best linear unbiased estimators

Roman Zmyślony, João T. Mexia, Francisco Carvalho, Inês J. Sequeira

Research output: Contribution to journalArticlepeer-review


The equivalence of ordinary least squares estimators (OLSE) and Gauss–Markov estimators for models with variance–covariance matrix (Formula presented.) is extended to derive a necessary and sufficient balance condition for mixed models with mean vector (Formula presented.) , with (Formula presented.) an incidence matrix, having OLSE for (Formula presented.) that are best linear unbiased estimator whatever the variance components. This approach leads to least squares like estimators for variance components. To illustrate the range of applications for the balance condition, interesting special models are considered.

Original languageEnglish
Pages (from-to)43-53
Number of pages11
JournalStatistical Papers
Issue number1
Publication statusPublished - 1 Mar 2016


  • Kruskal condition
  • OLSE
  • Orthogonal block structure models


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