Analysis

The framework for the analysis is Bayesian. The set of all data may be denoted , and the collection of parameters, . As referred to in Section  the method consists of the following:

1. Construct a model, obtaining a likelihood ;
2. Elicit a prior density ;
3. Deduce the posterior density ;
4. Estimate other quantities of practical interest, such as R(N).

• Likelihood
• Priors for the Parameters
  • Priors on , M and d.
• Evaluation of the Posterior distribution
• Evaluation of Other Quantities