Some Modified Integrated Squared Error Procedures for Multivariate Normal Data.

Abstract

A method of estimation for the parameters of the multivariate normal distribution based on the characteristic function (density) and its sample counterpart is given. These M-estimators are dependent on a user-specified parameter. The response of the parameter estimates and observation weights to variation of this user-specified parameter allows a sensitivity analysis of the data and the model considered as a single entity. The estimators have desirable robustness properties, are easy to compute and use, are relatively efficient at the multivariate normal and are useful in identifying potential outliers and problems with the statistical assumptions or the data. The method is extended to include multivariate experimental designs with attention restricted to the two-way cross classification. Several illustrations are provided. (Author)

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Document Details

Document Type
Technical Report
Publication Date
Jun 01, 1982
Accession Number
ADA119657

Entities

People

  • A. S. Paulson
  • C. E. Lawrence

Organizations

  • Rensselaer Polytechnic Institute

Tags

Communities of Interest

  • Biomedical

DTIC Thesaurus Topics

  • Algorithms
  • Classification
  • Computational Science
  • Computer Simulations
  • Covariance
  • Data Science
  • Delta Functions
  • Efficiency
  • Equations
  • Estimators
  • Gaussian Distributions
  • Military Research
  • New York
  • Normal Distribution
  • Statistical Algorithms
  • Statistical Samples
  • Two Dimensional

Fields of Study

  • Mathematics

Readers

  • Regression Analysis.
  • Statistical inference.