A Relationship between Generalized and Integrated Mean Squared Errors.

Abstract

Generalized mean squared error is a flexible measure of the adequacy of a regression estimator. It allows specific characteristics of the regression model and its intended use to be incorporated in the measure itself. Similarly, integrated mean squared error enables a researcher to stipulate particular regions of interest and weighting functions in the assessment of a prediction equation. The appeal of both measures is their ability to allow design or model characteristics to directly influence the evaluation of fitted regression models. In this note an equivalence of the two measures is established for correctly specified models. (Author)

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 1979
Accession Number
ADA071201

Entities

People

  • J. L. Hess
  • R. F. Gunst

Organizations

  • Southern Methodist University

Tags

DTIC Thesaurus Topics

  • Air Force
  • Coefficients
  • Computations
  • Data Science
  • Equations
  • Estimators
  • Guarantees
  • Information Science
  • Resilience
  • Scientific Research
  • Statistical Analysis
  • Statistics
  • Test And Evaluation
  • Universities
  • Weighting Functions

Fields of Study

  • Mathematics

Readers

  • Computational Modeling and Simulation
  • Statistical inference.