8.4 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,
andCaseBootstrapSampler
classes within theksl.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
andControlVariateDataCollector
can be very useful. Of course the classes for Monte Carlo integration within theksl.utilities.mcintegration
package could be useful. - Finally, for generation of multi-variate random variables, the classes within the
ksl.utilities.random.mcmc
andksl.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.