Probability pp 227-262 | Cite as

Statistical models

  • Anthony O’Hagan

Abstract

The techniques of Chapter 8 are extended in this chapter to cover the basic principles of statistical modelling. These ideas are discussed first in general terms in Section 9.1. Statistical analysis of data begins by representing the prior joint distribution of all the observations as having some simple structure conditional on certain unknown parameters. This is called a statistical model and is relatively objective. In contrast, the prior distribution of the parameters is typically subjective. Given sufficient observations, this prior distribution becomes dominated by the data, and the posterior distribution of the parameters is then essentially objective. This is the strength of statistical modelling.

Keywords

Posterior Distribution Prior Distribution Poisson Model Wheat Yield Empirical Distribution Function 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Copyright information

© A. O’Hagan 1988

Authors and Affiliations

  • Anthony O’Hagan
    • 1
  1. 1.University of WarwickUK

Personalised recommendations