Diagnostics and Robust Estimation When Transforming the Regression Model and the Response.

Abstract

In regression analysis, the response is often transformed to remove heteroscedasticity and/or skewness. When a model already exists for the untransformed response, then it can be preserved by applying the same transform to both the model and the response. This methodology which we call 'transform both sides' has been applied in several recent papers, and appears highly useful in practice. When a parametric transformation family such as the power transformations is used, then the transformation can be estimated by maximum likelihood. The MLE, however, is very sensitive to outliers. This article proposes diagnostics to indicate cases influential for the transformation or regression parameters. Also proposed it a robust bounded-influence estimator similar to the Kraskeer-Welsch regression estimator. Keywords: Heteroscedasticity; Maximum likelihood. (Author)

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Document Details

Document Type
Technical Report
Publication Date
Oct 01, 1986
Accession Number
ADA177531

Entities

People

  • David Ruppert
  • Raymond J. Carroll

Organizations

  • University of North Carolina at Chapel Hill

Tags

Communities of Interest

  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Air Force
  • Algorithms
  • Computer Science
  • Data Science
  • Estimators
  • Fish
  • Information Science
  • Maximum Likelihood Estimation
  • New York
  • North Carolina
  • Regression Analysis
  • Scientific Research
  • Skewness
  • Statistical Algorithms
  • Statistical Analysis
  • Statistical Inference
  • Statistics

Fields of Study

  • Mathematics

Readers

  • Regression Analysis.
  • Statistical inference.