DeterministicParticleResampler Class Reference

Inherits ParticleResampler.

Inheritance diagram for DeterministicParticleResampler:

[legend]List of all members.

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Detailed Description

Deterministic particle resampler.

Author:

Lawrence Murray <lawrence@indii.org>

Version:

Rev

404

Date:

Date

2008-03-05 14:52:55 +0000 (Wed, 05 Mar 2008)

Produces a new approximation of a weighted sample set using a set of equally weighted samples, possibly with duplication (Kitagawa 1996).

References

Kitagawa, G. Monte Carlo Filter and Smoother for Non-Gaussian Nonlinear State Space Models. Journal of Computational and Graphical Statistics, 1996, 5, 1-25.

Definition at line 27 of file DeterministicParticleResampler.hpp.

Public Member Functions
	DeterministicParticleResampler (const unsigned int P=0)
	Constructor.
virtual	~DeterministicParticleResampler ()
	Destructor.
void	setNumParticles (const unsigned int P=0)
	Set the number of particles to resample.
virtual indii::ml::aux::DiracMixturePdf	resample (indii::ml::aux::DiracMixturePdf &p)
	Resample the distribution.

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Constructor & Destructor Documentation

DeterministicParticleResampler

(

const unsigned int

P = 0

)

Constructor.

Parameters:

P

Number of particles to resample from each distribution supplied to resample(). If zero, will resample the same number of particles as the distribution supplied.

Definition at line 11 of file DeterministicParticleResampler.cpp.

~DeterministicParticleResampler

(

)

[virtual]

Destructor.

Definition at line 16 of file DeterministicParticleResampler.cpp.

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Member Function Documentation

void setNumParticles

(

const unsigned int

P = 0

)

Set the number of particles to resample.

Parameters:

P

Number of particles to resample from each distribution supplied to resample(). If zero, will resample the same number of particles as the distribution supplied.

Definition at line 20 of file DeterministicParticleResampler.cpp.

aux::DiracMixturePdf resample

(

indii::ml::aux::DiracMixturePdf &

p

)

[virtual]

Resample the distribution.

This produces a new approximation of the same distribution using a set of equally weighted sample points. Sample points are selected using the deterministic resampling method given in the appendix of Kitagawa (1996).

Returns:

The resampled distribution.

Implements ParticleResampler.

Definition at line 24 of file DeterministicParticleResampler.cpp.

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