Some Properties of Maximum Likelihood Strategy for Re-Pairing Broken Random Sample.

Abstract

Matching data from a bivariate population is considered when observations are available only in the form of a broken random sample. In other words, a random sample of n pairs is drawn from the population but the observed data consist of n observations on the second component and the n observations on an unknown permutation of the first component of the n pairs of data. A maximum likelihood matching strategy is revisited. The proportion of approximately correct matches (due to Yahav) is used to evaluate the performance of the pairing strategy as n approaches limit of infinity. The small sample behavior of this proportion is studied via a Monte-Carlo simulation in the special case of bivariate normal parent population. Keywords: Asymptotic properties; Statistical data; Tables(data).

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 1986
Accession Number
ADA186164

Entities

People

  • Prem K. Goel
  • T. Ramalingam

Organizations

  • Ohio State University

Tags

Communities of Interest

  • Counter IED
  • Human Systems

DTIC Thesaurus Topics

  • Data Science
  • Decision Theory
  • Indicators
  • Information Science
  • Monte Carlo Method
  • New York
  • Nonparametric Statistics
  • Notation
  • Order Statistics
  • Permutations
  • Probability
  • Random Variables
  • Sequences
  • Statistical Decision Theory
  • Statistical Samples
  • Statistics
  • Theorems

Fields of Study

  • Mathematics

Readers

  • Regression Analysis.
  • Statistical inference.