Classification and Estimation of Growth Curves, a Bayesian Approach,

Abstract

Classification of observations and estimation of parameters in growth curves are considered from a Bayesian viewpoint. The author considers two different covariance matrices, (1) Sigma arbitrary positive definite and (2) Sigma = X(Gamma)(X prime) + Z theta(Z prime), which was first considered by Rao, where X is p x m of rank m < p and Z is p x p - m such that (X prime)Z = 0.

Document Details

Document Type
Technical Report
Publication Date
Mar 01, 1975
Accession Number
ADA011594

Entities

People

  • Jack Chao
  • Seng Lee

Organizations

  • Air Force Research Laboratory

Tags

DTIC Thesaurus Topics

  • Bayesian Networks
  • Classification
  • Covariance
  • Data Science
  • Information Science
  • Observation

Fields of Study

  • Mathematics

Readers

  • Analytical Mechanics
  • Statistical inference.

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference