Maximum Likelihood Estimation with Incomplete Multinomial Data.

Abstract

When sampling from a multinomial population, it may happen either by chance or by design that some of the observations are only partially classified. In the paper the amount of information in the partially classified observation is evaluated, and maximum likelihood estimators are obtained using both completely classified and partially classified data. In general an iterative solution is required, but special cases are identified in which the solution is obtained in closed form. (Author)

Document Details

Document Type
Technical Report
Publication Date
Aug 01, 1971
Accession Number
AD0733051

Entities

People

  • H. H. Oxspring
  • R. R. Hocking

Organizations

  • Texas A&M University

Tags

DTIC Thesaurus Topics

  • Algorithms
  • Estimators
  • Mathematics
  • Maximum Likelihood Estimation
  • Measurement Transportation Algorithms
  • Observation
  • Optimal Estimators
  • Sampling
  • Statistical Algorithms

Fields of Study

  • Mathematics

Readers

  • Aviation Safety Risk Assessment.
  • Statistical inference.