Case
This class facilitates bootstrap sampling. The estimator provides the mechanism for estimating statistical quantities from the original data. From the data, it can produce 1 or more estimated quantities. Bootstrap estimates are computed on the observed estimates from each bootstrap sample. The specified stream controls the bootstrap sampling process.
Properties
If true, the stream will automatically participate in having its stream advanced to the next sub-stream via stream managers
Tells the stream to start producing antithetic variates
Returns an 2-D array representation of the estimates from the bootstrapping process. The rows of the array are the multi-variate estimates from each bootstrap sample. The columns of the array represent the bootstrap estimates for each dimension across all the bootstrap samples.
A list holding the observed frequencies of the cases within each bootstrap sample.
If the save bootstrap data option was not turned on during the sampling then the list returned is empty.
Statistics collected across each dimension based on the estimates computed from each bootstrap sample. These statistics are cleared whenever generateSamples() is invoked in order to report statistics on the newly generated bootstrap samples.
If true, the stream will automatically participate in having its stream reset to its start stream via stream managers
the underlying stream of random numbers
Functions
Positions the RNG at the beginning of its next sub-stream
This method changes the underlying state of the Bootstrap instance by performing the bootstrap sampling.
The resetStartStream method will position the RNG at the beginning of its stream. This is the same location in the stream as assigned when the RNG was created and initialized.
Resets the position of the RNG at the start of the current sub-stream
Assigns the stream associated with the supplied number from the default RNStreamProvider