Comparing Models with Experimental Results

  • James E. A. McIntosh
  • Rosalind P. McIntosh
Part of the Monographs on Endocrinology book series (ENDOCRINOLOGY, volume 16)


The subject of this chapter is parameter estimation, an essential part of any analytical experimentation. Such experimentation involves the following steps. Data is collected describing the variation of one component with another. A model is devised showing the proposed form of the interaction between the components, and an equation is written to describe it. Values of the parameters in the equation must then be estimated which are compatible with the data and its precision. For a model based on theory, the parameters have physical meaning. In the case of empirical models the equations are non-unique and can be modified in any way until suitable parameters are found; furthermore, the parameters have no physical meaning. In either case the equations representing the model become tenable only with the evaluation of feasible parameter values.


Objective Function Monte Carlo Simulation Condition Number Digital Computer Sensitivity Coefficient 
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.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Copyright information

© Springer-Verlag Berlin, Heidelberg 1980

Authors and Affiliations

  • James E. A. McIntosh
    • 1
  • Rosalind P. McIntosh
    • 2
  1. 1.Department of Obstetrics and GynaecologyUniversity of AdelaideAdelaideAustralia
  2. 2.Lucy Cavendish CollegeCambridgeUK

Personalised recommendations