title: Empirical Bayes estimation for combinations of multivariate bioassays.
abstract: This article presents a new empirical Bayes estimator (EBE) and a shrinkage estimator for determining the relative potency from several multivariate bioassays by incorporating prior information on the model parameters based on Jeffreys' rules. The EBE can account for any extra variability among the bioassays, and if this extra variability is 0, then the EBE reduces to the maximum likelihood estimator for combinations of multivariate bioassays. The shrinkage estimator turns out to be a compromise of the prior information and the estimator from each multivariate bioassay, with the weights depending on the prior variance.
authors: Department of Fisheries and Oceans, Government of Canada, Nanaimo, British Columbia. chend@dfo-mpo.gc.ca
authors: D G
authors: DG
authors: Chen
authors: E M
authors: EM
authors: Carter
authors: J J
authors: JJ
authors: Hubert
authors: P T
authors: PT
authors: Kim
mesh_terms: D000465:Algorithms; D001499:Bayes Theorem; D001681:Biological Assay / Q000706:statistics & numerical data*; D001699:Biometry; D016013:Likelihood Functions; D015233:Models, Statistical; D015999:Multivariate Analysis