A matrix approach to a general partitioned linear model with partial parameter restrictions
Rong Ma, Yongge Tian
Abstract
This article considers some fundamental estimation problems on a general partitioned linear model with partial parameter restrictions. We shall derive analytical formulas for calculating the ordinary least-squares estimators (OLSEs) and the best linear unbiased estimators (BLUEs) of the whole and partial parameter vectors in the model and its reduced models, and establish identifying conditions for the equivalence of the OLSEs and BLUEs under among these models.
Topics & Concepts
EstimatorApplied mathematicsMathematicsLinear modelEquivalence (formal languages)Ordinary least squaresEstimation theoryGeneralized least squaresMatrix (chemical analysis)Mathematical optimizationStatisticsDiscrete mathematicsComposite materialMaterials scienceMatrix Theory and AlgorithmsStatistical and numerical algorithmsBlind Source Separation Techniques