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

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 transforming both the model and the response with the same transformation. This methodology, is called transform both sides has been applied in several recent papers, and appears highly useful in practice. When a parametric transformation family such as 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 which indicate cases influential for the transformation regression parameters. We also propose a robust bounded-influence estimator similar to the Krasker-Welsch regression estimate. Both diagnostics and the robust estimator can be implemented on standard software. (Author)

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Document Details

Document Type
Technical Report
Publication Date
Oct 01, 1985
Accession Number
ADA171938

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
  • Computations
  • Covariance
  • Data Science
  • Data Sets
  • Engineering
  • Estimators
  • Fish
  • Fisheries
  • Information Science
  • Iterations
  • Maximum Likelihood Estimation
  • New York
  • North Carolina
  • Regression Analysis
  • Statistical Inference
  • Statistics

Fields of Study

  • Mathematics

Readers

  • Regression Analysis.