Weighted Least Squares Rank Estimates.

Abstract

In this paper rank estimates, called WLS rank estimates and computed using iteratively reweighted least squares, are studied. They do not require the estimation of auxilliary scale or slope parameters nor do they require numerical search techniques to minimize a convex surface. The price is a small asymptotic efficiency loss. In the location model, beginning with a resistant starting value such as the median, the WLS rank estimates have good robustness and computational properties. The WLS rank estimate is also extended to the regression model and an example is given. (Author)

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Document Details

Document Type
Technical Report
Publication Date
Jul 01, 1981
Accession Number
ADA102759

Entities

People

  • Kuo-sheuon Cheng
  • Thomas P. Hettmansperger

Organizations

  • Pennsylvania State University

Tags

DTIC Thesaurus Topics

  • Asymptotic Normality
  • Convergence
  • Data Science
  • Distribution Functions
  • Distribution Theory
  • Efficiency
  • Equations
  • Estimators
  • Information Science
  • Iterations
  • Linearity
  • Normal Distribution
  • Order Statistics
  • Probability
  • Statistical Algorithms
  • Statistics
  • Theorems

Fields of Study

  • Mathematics

Readers

  • Ballistic Missile Meteorology
  • Regression Analysis.
  • Statistical inference.