[Work Log] FIRE - streamlining; missing data

Refactored kjb::Matrix::resize to be re-use allocated space under more circumstances. This is currently a bottleneck in inference, and signficantly improves runtime.

Implemented Missing data handling:

1. Likelihood ignores missing values
2. initial model estimation handles gracefully handles missing data

TODO: Test missing data. Randomly convert observations to missing, see if cluster parameters and memberships are still correctly estimated. Is there a "critical point" above which missing data ruins results?