Package dev.nm.stat.random.sampler.resampler.bootstrap

Class CaseResamplingReplacementForObject<X>

java.lang.Object

dev.nm.stat.random.sampler.resampler.bootstrap.CaseResamplingReplacementForObject<X>

All Implemented Interfaces:

ObjectResampler<X>, Seedable

public class CaseResamplingReplacementForObject<X>
extends Object
implements ObjectResampler<X>

This is the classical bootstrap method described in the reference. It draws from the original sample with replacement. This implementation is thread-safe that allows concurrent access to newResample() by multiple threads.

See Also:

• • "B. Efron and R. Tibshirani. An Introduction to the Bootstrap. 1993. Chapman and Hall, New York, London."
  • Wikipedia: http://en.wikipedia.org/wiki/Bootstrapping_(statistics)#Case_resampling

Field Summary

Fields

Modifier and Type	Field	Description
static final int	DEFAULT_CACHE_SIZE	The default cache size = the number of available processors × 1000.

Constructor Summary

Constructors

Constructor	Description
CaseResamplingReplacementForObject(X[] sample, Class<X> clazz)	Constructs a bootstrap sample generator.
CaseResamplingReplacementForObject(X[] sample, Class<X> clazz, ConcurrentCachedRLG rlg)	Constructs a bootstrap sample generator.
CaseResamplingReplacementForObject(X[] sample, Class<X> clazz, RandomLongGenerator uniform)	Constructs a bootstrap sample generator.

Method Summary

Modifier and Type	Method	Description
X[]	newResample()	Gets a resample from the original sample.
void	seed(long... seeds)	Seed the random number/vector/scenario generator to produce repeatable experiments.

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Field Details

DEFAULT_CACHE_SIZE

public static final int DEFAULT_CACHE_SIZE

The default cache size = the number of available processors × 1000.

Constructor Details

CaseResamplingReplacementForObject

public CaseResamplingReplacementForObject(X[] sample,
 Class<X> clazz)

Constructs a bootstrap sample generator. This is the classical bootstrap with replacement.

Parameters:

sample - the original sample

clazz - the class of the sample objects

CaseResamplingReplacementForObject

public CaseResamplingReplacementForObject(X[] sample,
 Class<X> clazz,
 RandomLongGenerator uniform)

Constructs a bootstrap sample generator. This is the classical bootstrap with replacement.

Parameters:

sample - the original sample

clazz - the class of the sample objects

uniform - a uniform random long generator

CaseResamplingReplacementForObject

public CaseResamplingReplacementForObject(X[] sample,
 Class<X> clazz,
 ConcurrentCachedRLG rlg)

Constructs a bootstrap sample generator. This is the classical bootstrap with replacement.

Parameters:

sample - the original sample

clazz - the class of the sample objects

rlg - a concurrent uniform random long generator

Method Details

seed

public void seed(long... seeds)

Description copied from interface: Seedable

Seed the random number/vector/scenario generator to produce repeatable experiments.

Specified by:

seed in interface Seedable

Parameters:

seeds - the seeds

newResample

public X[] newResample()

Description copied from interface: ObjectResampler

Gets a resample from the original sample. It is very important this method is thread-safe so resampling can be run in parallel.

Specified by:

newResample in interface ObjectResampler<X>

Returns:

a resample, e.g., a bootstrap sample