Solving problems in parameter redundancy using computer algebra

E. A. Catchpole, B. J. T. Morgan and A. Viallefont

Journal of Applied Statistics, 2002, vol. 29, issue 1-4, 625-636

Abstract: A model, involving a particular set of parameters, is said to be parameter redundant when the likelihood can be expressed in terms of a smaller set of parameters. In many important cases, the parameter redundancy of a model can be checked by evaluating the symbolic rank of a derivative matrix. We describe the main results, and show how to construct this matrix using the symbolic algebra package Maple. We apply the theory to examples from the mark-recapture field. General code is given which can be applied to other models.

Date: 2002
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DOI: 10.1080/02664760120108601

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