On Minimum Cramer-von Mises-Norm Parameter Estimation.

Abstract

Minimum distance parameter estimation using weighted Cramer-von Mises statistics is considered for the general one-dimensional case. Under rather general conditions, the derived estimators are asymptotically normal. Consideration is given to appropriate weights to produce Fisher-efficient estimators. In fact, estimators can be obtained with influence curves proportional to any desired smooth function, and hence prescribed first-order robustness properties. Many such curves (any 'redescending' influence curve) are shown to require weight functions which take on negative values. (Author)

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Document Details

Document Type
Technical Report
Publication Date
Oct 01, 1980
Accession Number
ADA091519

Entities

People

  • T. De Wet
  • W. C. Perr

Organizations

  • Southern Methodist University

Tags

DTIC Thesaurus Topics

  • Abstracts
  • Computations
  • Data Science
  • Distribution Functions
  • Equations
  • Estimators
  • Information Science
  • Mathematics
  • Normal Distribution
  • Optimal Estimators
  • Order Statistics
  • Simultaneous Equations
  • Statistical Algorithms
  • Statistical Analysis
  • Statistical Functions
  • Statistics
  • Theorems

Fields of Study

  • Mathematics

Readers

  • Statistical inference.