Sufficent conditions for orthogonal designs in mixed linear models

DOI10.1016/S0378-3758(98)00071-8zbMath0933.62069WikidataQ127360599 ScholiaQ127360599MaRDI QIDQ1299101

Dawn M. VanLeeuwen, David S. Birkes, Justus F. Seely

Publication date: 9 April 2000

Published in: Journal of Statistical Planning and Inference (Search for Journal in Brave)

zbMATH Keywords

orthogonal designorthogonal block structurecommutative quadratic subspacemixed linear models

Mathematics Subject Classification ID

Design of statistical experiments (62K99) Combinatorial aspects of block designs (05B05) Statistical block designs (62K10) Analysis of variance and covariance (ANOVA) (62J10)

Related Items (13)

Minimum variance unbiased invariant estimation of variance components under normality ⋮ Binary operations on orthogonal models, application to prime basis factorials and fractional replicates ⋮ Estimation in models with commutative orthogonal block structure ⋮ On nested block designs geometry ⋮ Inference forLorthogonal models ⋮ The equality of REML and ANOVA estimators of variance components in unbalanced normal classification models ⋮ Nesting segregated mixed models ⋮ Complete and sufficient statistics and perfect families in orthogonal and error orthogonal normal models ⋮ Best Unbiased Estimation in Unbalanced Split Plot Designs ⋮ Binary operations and canonical forms for factorial and related models ⋮ Balance and orthogonality in designs for mixed classification models ⋮ Inference for types and structured families of commutative orthogonal block structures ⋮ Mean driven balance and uniformly best linear unbiased estimators

Cites Work

• Balance in designed experiments with orthogonal block structure
• What is an analysis of variance?
• Theorems Concerning Eisenhart's Model II
• When are Gauss-Markov and Least Squares Estimators Identical? A Coordinate-Free Approach
• On Canonical Forms, Non-Negative Covariance Matrices and Best and Simple Least Squares Linear Estimators in Linear Models
• Quadratic Subspaces and Completeness
• Completeness for a Family of Multivariate Normal Distributions
• The analysis of randomized experiments with orthogonal block structure. I. Block structure and the null analysis of variance
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