On the Estimation of a Variance Ratio.

Abstract

The estimation of the ratio of two independent normal variances is considered under scale invariant squared error loss function, when the means are unknown. The best invariant estimator is shown to be inadmissible. Two new classes of improved estimators are obtained, one by extending Stein (1964) and the other by extending Brown (1968). Numerical studies are presented to indicate the percent improvements in risk.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Apr 06, 1988
Accession Number
ADA193190

Entities

People

  • Alan E. Gelfand
  • Dipak K. Dey

Organizations

  • Stanford University

Tags

Communities of Interest

  • C4I
  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Algorithms
  • Data Science
  • Estimators
  • Information Science
  • Mathematics
  • Military Research
  • Monte Carlo Method
  • New York
  • Normal Distribution
  • Probability
  • Statistical Algorithms
  • Statistical Samples
  • Statistics
  • Theorems
  • United States
  • United States Government
  • Universities

Fields of Study

  • Mathematics

Readers

  • Statistical inference.

Technology Areas

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