Simple BAN Estimators of Correlations for Certain Multivariate Normal Models with Known Variances.

Abstract

It is well-known that in certain multivariate normal models with known variances, maximum likelihood estimation of correlations is arithmetically cumbersome. For many of these models, the author gives a technique to obtain estimators which are relatively simple functions of the sufficient statistics and are BAN. The procedure makes use of the fact that many of the likelihood equations for these models are essentially cubic equations. For the associated cubic equation, an explicit solution is found which is consistent for the parameter to be estimated. The author is then able to show that this solution has the appropriate asymptotic efficiency and normality properties. Considered in detail are the intraclass, autoregressive, and moving average models.

Document Details

Document Type
Technical Report
Publication Date
Feb 01, 1975
Accession Number
ADA008390

Entities

People

  • Allan R. Sampson

Organizations

  • Florida State University

Tags

DTIC Thesaurus Topics

  • Algorithms
  • Computing-Related Activities
  • Data Science
  • Efficiency
  • Equations
  • Estimators
  • Information Science
  • Interdisciplinary Science
  • Mathematical Analysis
  • Mathematics
  • Maximum Likelihood Estimation
  • Normality
  • Numerical Analysis
  • Statistical Algorithms
  • Statistical Analysis
  • Statistics

Fields of Study

  • Mathematics

Readers

  • Calculus or Mathematical Analysis
  • Regression Analysis.
  • Statistical inference.