Description Slots Methods Author(s)

Basic class to implement a Sequential Monte Carlo sampler.

particles = "ANY", logWeights = "vector", # log of particle weights unifWeights = "logical", # are current weights uniform? p_move = "function", lW_update = "function", logLik = "function", resampleC = "numeric", N = "integer"

`particles`

:Set of particles. Format depends on implementation.

`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`

.`logLik`

:Function to compute the

`logLik`

.`resampleC`

:Numeric value (between 0 and 1) indicating when to perform resampling.

`N`

:Integer indicating the total number of particles.

- particles
`signature(object = "ParticleBase")`

: return particles- particles<-
`signature(object = "ParticleBase")`

: set particles- ParticleMove
`signature(object = "ParticleBase")`

: move particles

#

- doParticleMove
`signature(object = "ParticleBase")`

: move particles- SmcIterate
`signature(object = "ParticleBase")`

: perform a full SMC iteration

#

- doSmcIterate
`signature(object = "ParticleBase")`

: move particles- UpdateWeights
`signature(object = "ParticleBase")`

: update weights

#

- doUpdateWeights
`signature(object = "ParticleBase")`

: move particles- ESS
`signature(object = "ParticleBase")`

: Effective Sample Size- logWeights
`signature(object = "ParticleBase")`

: get the log of the particles weights- logWeights<-
`signature(object = "ParticleBase")`

: set the log of the particles weights

#

- getLogWeights
`signature(object = "ParticleBase")`

: move particles

#

- setLogWeights
`signature(object = "ParticleBase")`

: move particles- getWeights
`signature(object = "ParticleBase")`

: get the exponentiated (unnormalized) weights- getNormWeights
`signature(object = "ParticleBase")`

: get the normalized weights

Maarten Speekenbrink

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