ABSTRACT
In Chapter 4 we saw that, for logistic regression, it was not possible to analytically obtain the posterior density over the model parameters. We described how to overcome this problem with three alternatives: the MAP solution (a point estimate of the parameters that maximises the posterior), the Laplace approximation (where the posterior is approximated with a Gaussian density) and sampling from the posterior using the Metropolis-Hastings algorithm.
