STATISTICAL DESIGN OF COMPLEX EXPERIMENTAL PROGRAMS. I. OPTIMUM EXPERIMENTAL DESIGNS OBTAINED BY MINIMIZING A LOSS FUNCTION

Abstract

A loss function balancing the value of information against the cost of experimentation is presented for the case of the m variable linear regression model when experimental costs are a function of the point at which the experiment is performed. Solutions in certain special cases are presented. (Author)

Document Details

Document Type
Technical Report
Publication Date
Jul 01, 1962
Accession Number
AD0289283

Entities

People

  • Kenneth W. Last

Organizations

  • Rocketdyne

Tags

DTIC Thesaurus Topics

  • Computing-Related Activities
  • Data Science
  • Experimental Design
  • Information Science
  • Interdisciplinary Science
  • Mathematical Analysis
  • Mathematics

Fields of Study

  • Mathematics

Readers

  • Regression Analysis.
  • Software Engineering

Technology Areas

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