9.4 Summary

The KSL provides classes within the \(ksl.utilities\) package that facilitate the generation and analysis of situations involving advanced Monte Carlo Techniques. The key classes that you should remember include:

• For bootstrapping work, you will use the Bootstrap, BootstrapSampler, and CaseBootstrapSampler classes within the ksl.utilities.statistics package
• For variance reduction work, you should review random number streams, their creation and usage. In addition, the classes to collect data from the simulation such as ReplicationDataCollector and ControlVariateDataCollector can be very useful. Of course the classes for Monte Carlo integration within the ksl.utilities.mcintegration package could be useful.
• Finally, for generation of multi-variate random variables, the classes within the ksl.utilities.random.mcmc and ksl.utilities.rvariable packages, that are especially designed for dealing with generating arrays of data should be noted.

As you can see, the KSL provides many immediately useful implementations for advanced Monte Carlo work and a library structure that facilitates the development of additional implementations.