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Introduction to Fraser (1966) Structural Probability and a Generalization

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Book cover Breakthroughs in Statistics

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Abstract

This paper defines structural probability and develops its interpretation through the introduction of an error variable. The formulation of the observed data as having been generated by a combination of an error variable and an unknown parameter has come to be called the structural model, and inference based on this model structural inference.

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Author information

Authors and Affiliations

  1. University of Toronto, USA

    Nancy Reid

Authors
  1. Nancy Reid
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Editor information

Editors and Affiliations

  1. College of Business and Management, University of Maryland at College Park, College Park, MD, 20742, USA

    Samuel Kotz

  2. Department of Statistics Phillips Hall, The University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA

    Norman L. Johnson

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© 1992 Springer Science+Business Media New York

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Reid, N. (1992). Introduction to Fraser (1966) Structural Probability and a Generalization. In: Kotz, S., Johnson, N.L. (eds) Breakthroughs in Statistics. Springer Series in Statistics. Springer, New York, NY. https://doi.org/10.1007/978-1-4612-0919-5_35

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  • DOI: https://doi.org/10.1007/978-1-4612-0919-5_35

  • Publisher Name: Springer, New York, NY

  • Print ISBN: 978-0-387-94037-3

  • Online ISBN: 978-1-4612-0919-5

  • eBook Packages: Springer Book Archive

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