Likelihood functions and some maximum likelihood estimators for symbolic data

J. Le-Rademacher, L. Billard

Research output: Contribution to journalArticle

20 Scopus citations

Abstract

Likelihood functions are the foundation of many statistical methodologies in classical data analysis. Likelihood functions for symbolic data must be introduced before these classical methods can be extended to the analysis of symbolic data. In this paper, we propose the likelihood function for symbolic data and illustrate its applications by finding the maximum likelihood estimators for the mean and the variance of three common types of symbolic-valued random variables: interval-valued, histogram-valued and triangular-distribution-valued variables.

Original languageEnglish (US)
Pages (from-to)1593-1602
Number of pages10
JournalJournal of Statistical Planning and Inference
Volume141
Issue number4
DOIs
StatePublished - Apr 1 2011

Keywords

  • Histogram-valued data
  • Interval-valued data
  • Likelihood functions
  • Maximum likelihood estimators
  • Symbolic data analysis
  • Triangular-distribution-valued data

ASJC Scopus subject areas

  • Statistics and Probability
  • Statistics, Probability and Uncertainty
  • Applied Mathematics

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