new method (of Model class) to calculate log likelihood

[drbenvincent]

Write a method in the Model class to return the log likelihood of the data. This will be useful in general, but I'm doing this to resolve model comparison as part of #57.

It's basically just correct use of bernoulli.logpmf(responses, predicted_response_probabilities).

• responses will be a vector of T binary responses
• predicted_response_probabilities is what it sounds like. But it will be a matrix of size [T, P] where T is number of trials and P is number of particles. Although it will be a vector length T if we want to just use the median parameter estimates for example. Maybe have this as an option through a keyword argument in the method call.

[drbenvincent]

Silly me. We already have this as Model.log_likelihood but the implementation is a bit hacky.

[drbenvincent]

The implementation was not wrong before. But now it's slightly improved and clearer with explicit use of the Bernoulli logpmf.