Maximum Likelihood Estimation Using Bayesian Monte Carlo Methods
The objective of this thesis is to give a general account of the MCMC estimation approach dubbed data cloning, specically performing maximum likelihood estimation via Bayesian Monte Carlo methods. An account of the procedure will be given, and it will applied to four dierent maximum likelihood estimation problems: simple linear regression, multiple linear regression, a stochastic dynamical model (