Let's start our discussion of inference engines with the non-Markovian methods. Under some circumstances, these methods can provide a fast and accurate enough approximation to the posterior.
Non-Markovian methods
Grid computing
Grid computing is a simple brute-force approach. Even if you are not able to compute the whole posterior, you may be able to compute the prior and the likelihood point-wise; this is a pretty common scenario, if not the most common one. Let's assume we want to compute the posterior for a single parameter model, the grid approximation is as follows:
- Define a reasonable interval for the parameter (the prior should give you a hint).
- Place a grid of points (generally equidistant) on that interval...
