Residuals in Nonlinear Regression.

Abstract

The authors employ a quadratic expansion to investigate the behavior of the ordinary residuals in nonlinear regression. In particular, they derive quadratic approximations for the mean and variance of the ordinary residuals, and the covariances between the ordinary residuals and the fitted values. This investigation leads to the conclusion that the ordinary residuals can produce misleading results when used in diagnostic methods analogous to those for linear regression. Consequently, a new type of residual that overcomes many of the potential shortcomings of the ordinary residuals is suggested. (Author)

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 1984
Accession Number
ADA139309

Entities

People

  • C. L. Tsai
  • R. D. Cook

Organizations

  • University of Wisconsin–Madison

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  • Computational Science
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  • New York
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  • Regression Analysis
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Fields of Study

  • Mathematics

Readers

  • Approximation Theory.
  • Calculus or Mathematical Analysis
  • Theoretical Analysis.