Large Sample Behavior in Bayesian Analysis of Nonlinear Regression Models

In this paper we examine the large sample behavior of Bayesian posterior distributions in a nonlinear regression model. In particular, we seek Bayesian forms of consistency for parameter estimation problems. We derive here convergence and rate of convergence results for independent, identically distributed error models. The rate of convergence results are based on large deviation ideas.