Selecting Representative Points in Normal Populations.

Abstract

Quantization of the univariate normal arises in a number of applications. One seeks an optimal set of representative points and a number of investigators have written on this problem and prepared tables. In this paper we explore some special cases in two and three dimensions employing mean square error as a loss function. Results are given for these special multivariate situations. (Author)

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Document Details

Document Type
Technical Report
Publication Date
Jan 14, 1983
Accession Number
ADA125770

Entities

People

  • H. Solomon
  • S. Iyengar

Organizations

  • Stanford University

Tags

Communities of Interest

  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Data Analysis
  • Distribution Functions
  • Electrical Engineering
  • Engineering
  • Information Theory
  • Intervals
  • Military Research
  • New Jersey
  • New York
  • Normal Distribution
  • Numerical Integration
  • Probability
  • Random Variables
  • Simulations
  • Statistics
  • Symmetry
  • United States

Fields of Study

  • Mathematics

Readers

  • Approximation Theory.
  • Theoretical Analysis.

Technology Areas

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