Description Slots Methods Author(s)
Basic class to implement a Sequential Monte Carlo sampler.
Code: N lW_update logLik logWeights mcmc_move p_margin p_move particles resampleC unifWeights Inherited: particles logWeights unifWeights p_move mcmc_move lW_update logLik resampleC N Docs: Particles codep_margin: lW_update logWeights mcmc_move p_move resampleC unifWeights
particles
:Matrix with particle values
p_margin
:Integer indicating which margin in the matrix represents particle ids
logWeights
:Vector containing the log (unnormalised) particle weights.
unifWeights
Logical indicating whether the logWeights are uniform.
p_move
:Function to move the particles to a new position.
mcmc_move
:Function to perform a Monte Carlo Markov Chain move.
lW_update
:Function to do update the logWeights
.
resampleC
:Numeric value (between 0 and 1) indicating when to perform resampling.
signature(object = "ParticleMatrix")
: return particles
signature(object = "ParticleMatrix")
: set particles
signature(object = "ParticleMatrix")
: move particles
#
signature(object = "ParticleMatrix")
: move particles
signature(object = "ParticleMatrix")
: do a full SMC iteration
#
signature(object = "ParticleMatrix")
: move particles
signature(object = "ParticleMatrix")
: calculate updated weights
#
signature(object = "ParticleMatrix")
: move particles
signature(object = "ParticleMatrix")
: effective sample size
signature(object = "ParticleMatrix")
: return log weights
signature(object = "ParticleMatrix")
: set log weights
signature(object = "ParticleMatrix")
: return the unnormalized weights
signature(object = "ParticleMatrix")
: return the self-normalized weights
signature(object = "ParticleMatrix")
: return the estimated mean of each particle dimension
signature(object = "ParticleMatrix")
: return the estimated variance of each particle dimension
signature(object = "ParticleMatrix")
: return the estimated covariance matrix of the particle dimensions
Maarten Speekenbrink
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