SSMProblems.AbstractStateSpaceModel
— Typediff --git a/previews/PR16/index.html b/previews/PR16/index.html index fd81cf9..d2560c6 100644 --- a/previews/PR16/index.html +++ b/previews/PR16/index.html @@ -25,4 +25,4 @@ particles[i] = transition!!(rng, t, particles[i]) logweights[i] += emission_logdensity(t, particles[i]) end -end
SSMProblems.AbstractStateSpaceModel
— TypeSSMProblems.dimension
— Methoddimension(::Type{AbstractStateSpaceModel})
Returns the dimension of the state space for a given model type
SSMProblems.emission_logdensity
— Functionemission_logdensity(step, model, particle[, cache])
Compute the log potential of current particle. This effectively "reweight" each particle.
SSMProblems.isdone
— Functionisdone(step, model, particle[, cache])
Determine whether we have reached the last time step of the Markov process. Return true
if yes, otherwise return false
.
SSMProblems.transition!!
— Functiontransition!!(rng, step, particle[, cache])
Simulate the particle for the next time step from the forward dynamics.
SSMProblems.transition_logdensity
— Functiontransition_logdensity(step, model, particle, x[, cache])
(Optional) Computes the log-density of the forward transition if the density is available.
Murray, Lawrence & Lee, Anthony & Jacob, Pierre. (2013). Rethinking resampling in the particle filter on graphics processing
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This document was generated with Documenter.jl version 0.27.25 on Monday 24 July 2023. Using Julia version 1.9.2.