Estimation for Dirichlet Mixed Models

Abstract

Dirichlet mixed models find wide application and the estimation of these models is usually achieved through the method of moments. We present an iterative hybrid algorithm for obtaining the (MLE) maximum likelihood estimate employing both modified Newton-Raphson and E-M (electro-magnetics) methods. This successful MLE algorithm enables calculation of a jackknife MLE. Simulation comparison of the three estimates is provided. The MLE substantially improves upon the moments estimator particularly with increasing dimension and the jackknife MLE in turn offers a more dramatic improvement. Keywords: Comparison of estimates, Mixed moments, Moment estimator.

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Document Details

Document Type
Technical Report
Publication Date
May 19, 1990
Accession Number
ADA223583

Entities

People

  • Alan E. Gelfand
  • Steve Leeds

Organizations

  • Stanford University

Tags

DTIC Thesaurus Topics

  • Algorithms
  • Computational Science
  • Computations
  • Data Science
  • Equations
  • Estimators
  • Information Science
  • Maximum Likelihood Estimation
  • Method Of Moments
  • Probability
  • Probability Density Functions
  • Probability Distributions
  • Random Variables
  • Simulations
  • Statistical Algorithms
  • Statistical Analysis
  • Statistics

Fields of Study

  • Mathematics

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Statistical inference.
  • Systems Analysis and Design