Rank-Based Inference without Symmetric Errors.

Abstract

Statistical inference based on ranks is reviewed. The role of a parameter and methods for its estimation are discussed. In particular, the use of density estimation methods is shown to provide a consistent estimate without the assumption of symmetry of the underlying distribution. The use of a consistent estimate in constructing hypothesis tests in the linear model without assuming symmetry is discussed.

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Document Details

Document Type
Technical Report
Publication Date
Jun 01, 1982
Accession Number
ADA116432

Entities

People

  • James C. Aubuchon
  • Thomas P. Hettmansperger

Organizations

  • Pennsylvania State University

Tags

DTIC Thesaurus Topics

  • Contamination
  • Data Science
  • Distribution Functions
  • Distribution Theory
  • Efficiency
  • Estimators
  • Information Science
  • Intervals
  • New York
  • Normal Distribution
  • Pennsylvania
  • Probability
  • Probability Density Functions
  • Random Variables
  • Statistical Inference
  • Statistics
  • Theorems

Fields of Study

  • Mathematics

Readers

  • Statistical inference.

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference