Signal Model Analysis Via Model-Critical Methods

Abstract

Model-critical procedures provided a means to scrutinize an assumed parametric statistical model by varying the way the data is processed for repeated fits to the model. The criticism of the data is accomplished using the generalized likelihood function for the assumed probability density of the data. The degree of criticism if controlled by a user specified constant c. The model- critical parameter estimates are obtained by maximization of the generalized likelihood function. When c = O, no criticism is performed and maximum likelihood estimates are obtained. These procedures can indicated if any model assumptions have been violated. Model critical estimation procedures are presented for autoregressive (AR) models. The analysis of an AR example is presented. Keywords: Reprints.

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Document Details

Document Type
Technical Report
Publication Date
Oct 06, 1988
Accession Number
ADA200685

Entities

People

  • Albert S. Paulson
  • Gerald R. Swope

Organizations

  • Naval Underwater Systems Center

Tags

Communities of Interest

  • Ground and Sea Platforms
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Data Science
  • Engineering
  • Equations
  • Estimators
  • Experimental Design
  • Information Science
  • Information Theory
  • Maximum Likelihood Estimation
  • New York
  • Observation
  • Operations Research
  • Probability
  • Probability Distributions
  • Random Variables
  • Spectra
  • Statistical Algorithms
  • Statistics

Fields of Study

  • Mathematics

Readers

  • Regression Analysis.
  • Statistical inference.