Some Robust Estimates of Covariance Structure Based on Parametric Density Estimation.

Abstract

A new family of Fourier-based estimators of the parameters of the multivariate Gaussian distribution is presented. The estimators are equivalent to parametric density estimators. Three distinct estimators arise, each of which is robust and reduces to the maximum likelihood estimator as a special case. By varying the window width of a parametric density estimator, a set of diagnostics which are useful in problems of outlier detection and clustering are obtained. An example, using a trivariate data set, is given. Keywords: Covariance matrices.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Jan 01, 1987
Accession Number
ADA178806

Entities

People

  • A. S. Paulson
  • N. J. Delaney
  • T. A. Delehanty

Tags

Communities of Interest

  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Algorithms
  • Anomaly Detection
  • Change Detection
  • Chemical Analysis
  • Clustering
  • Covariance
  • Data Analysis
  • Data Science
  • Data Sets
  • Detection
  • Estimators
  • Information Science
  • New York
  • Probability
  • Statistical Algorithms
  • Statistical Data
  • Statistics

Fields of Study

  • Mathematics

Readers

  • Statistical inference.