Optimal Allocation of Experimental Material.

Abstract

The problem considered is that of how to allocate optimally a fixed number of experimental units to a given number of treatments when there are covariates and the values of the covariates are known prior to the advent of the actual experiment. The underlying statistical model is assumed to be linear in all its parameters, and the criterion of optimality was, for the most part, taken to be D-optimality for inferences on the treatment 'means'. An allocation of the experimental units is shown to be optimal according to this criterion if and only if it is D-optimal for inferences on all parameters. It is shown that the computations required to determine an optimal allocation can be simplified by taking advantage of known results on the determinants of partitioned matrices. D-optimal designs were computed for a simple example taken from the chemical industry, and it was found that, at least in some instances, their use would result in a considerable increase in efficiency over choosing an allocation by randomization. (Modified author abstract)

Document Details

Document Type
Technical Report
Publication Date
Jul 01, 1973
Accession Number
AD0765169

Entities

People

  • David A. Harville

Organizations

  • Air Force Research Laboratory

Tags

DTIC Thesaurus Topics

  • Abstracts
  • Chemical Industry
  • Computations
  • Efficiency

Fields of Study

  • Mathematics

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Operations Research
  • Regression Analysis.

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference
  • AI & ML - Machine Learning Algorithms