### Department of Biostatistics Seminar/Workshop Series

# **Advantages of Transformation in Constrained Parameter Problems**** **

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**## Anindya Roy, PhD

##### Professor, Department of Mathematics and Statistics, University of Maryland, Baltimore County

**Advantages of Transformation in Constrained Parameter Problems**
In many applications, the underlying scientific theory may impose natural constraints on the parameters of commonly used models. While it is a good practice to maintain the constraints in any inferential procedure related to the parameters, it may turn out to be an extremely difficult proposition due to complexity of the constraints. In such situations, it helps to reparameterize the problem in terms of parametric functions that are free of constraints or at least have constraints that are more tractable. We will illustrate the advantages of making parameter transformation in the context of some messy constrained parameter problems.
-- AudreyCarvajal - 25 Nov 2013 **
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