The Duality of Diagnostic Checking and Robustification in Model Building: Some Considerations and Examples.

Abstract

Consideration is given to the means by which appropriate diagnostic checking functions of the data can be developed to guard against feared model discrepancies. A formal basis for the selection of a function is given for situations where the feared inadequacy can be characterized by a discrepancy parameter beta which takes a (possible inappropriate) value of beta sub zero in the model. The relationship of this checking function with the posterior distribution obtained from an elaborated ('robustified') model which allows for the discrepancy parameter to be estimated is discussed. The nature of the diagnostic check is briefly described for problems relating to transformation of the dependent variable and to serial correlation; while a more thorough investigation of the checking function is given for problems relating to outlying observations and to transformation of predictor variables. Several examples are given to illustrate these ideas.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Jun 01, 1980
Accession Number
ADA089643

Entities

People

  • George E. P. Box
  • Steven P. Bailey

Organizations

  • University of Wisconsin–Madison

Tags

Communities of Interest

  • C4I
  • Ground and Sea Platforms

DTIC Thesaurus Topics

  • Analysis Of Variance
  • Bayesian Inference
  • Bayesian Networks
  • Combinatorial Analysis
  • Contracts
  • Data Analysis
  • Data Mining
  • Data Science
  • Data Sets
  • Information Science
  • Mathematics
  • Normal Distribution
  • Observation
  • Probability
  • Statistical Algorithms
  • Statistical Analysis
  • Statistics

Fields of Study

  • Mathematics

Readers

  • Statistical inference.
  • Theoretical Analysis.