Nonlinear Statistical Estimation with Numerical Maximum Likelihood

Abstract

The topics of maximum likelihood estimation and nonlinear programming are developed thoroughly with emphasis on the numerical details of obtaining estimates from highly nonlinear models. Parametric estimation is discussed with the three parameter Weibull family of densities serving as an example. A general nonlinear programming method is discussed for both first and second order representations of the maximum likelihood estimaton, as well as a hybrid of both approaches. A new class of constrained parametric estimators is introduced with numerical methods for their determination. Structural estimation with maximum likelihood is examined, and a Bernoulli regression technique is presented.

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Document Details

Document Type
Technical Report
Publication Date
Oct 01, 1974
Accession Number
ADA001743

Entities

People

  • Gerald G. Brown

Organizations

  • University of California, Los Angeles

Tags

Communities of Interest

  • Advanced Electronics
  • Air Platforms
  • Space
  • Weapons Technologies

DTIC Thesaurus Topics

  • Computational Fluid Dynamics
  • Computational Science
  • Computer Programs
  • Data Science
  • Discriminant Analysis
  • Evolutionary Algorithms
  • Information Science
  • Knowledge Management
  • Linear Programming
  • Mathematical Models
  • Maximum Likelihood Estimation
  • Operations Research
  • Optimization
  • Statistical Algorithms
  • Statistical Analysis
  • Statistical Inference
  • Surveys

Fields of Study

  • Mathematics

Readers

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