Maximum Likelihood Estimation of Functional Relationships

Maximum Likelihood Estimation of Functional Relationships by Nico J.D. Nagelkerke.

The theory of functional relationships concerns itself with inference from models with a more complex error structure than those existing in regression models. We are familiar with the bivariate linear relationship having measurement errors in both variables and the fact that the standard regression...

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Bibliographic Details
Main Author: Nagelkerke, Nico J.D (Author)
Corporate Author: SpringerLink (Online service)
Format: eBook
Language:English
Published: New York, NY : Springer New York : Imprint: Springer, 1992.
Edition:1st ed. 1992.
Series:Lecture Notes in Statistics, 69
Springer eBook Collection.
Subjects:
Applied mathematics.
Engineering mathematics.
Electronic resources (E-books)
Online Access:Click to view e-book
Holy Cross Note:Loaded electronically.
Electronic access restricted to members of the Holy Cross Community.
Table of Contents:
  • 1:Introduction
  • I.Introduction
  • II.Inference
  • III.Controlled variables
  • IV.Outline of the following chapters
  • 2:Maximum likelihood estimation of functional relationships
  • I.Introduction
  • II.Maximization of the likelihood under constraints
  • III.The conditional likelihood
  • IV.Maximum likelihood estimation for multivariate normal distributions with known covariance matrix
  • V.Maximum likelihood estimation for multivariate normal distributions with unknown covariance matrix
  • VI.Covariance matrix of estimators
  • VII.Error distributions depending on the true variables
  • VIII.Proportion of explained variation
  • 3:The multivariate linear functional relationship
  • I.Introduction
  • II.Identifiability
  • III.Heteroscedastic errors
  • IV.Homoscedastic errors
  • V.Factor space
  • VI.The asymptotic distribution of the parameter estimators
  • VII.Replicated observations
  • VIII.Instrumental variables
  • References.

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