CBSPF: Conditional Backward Sampling Particle Filter

In jeremyhengjm/UnbiasedScore: Unbiased estimators for partially observed diffusions

Conditional Backward Sampling Particle Filter

Description

Runs a conditional particle filter with backward sampling (Whiteley, 2010).

Usage

CBSPF(
  model,
  theta,
  discretization,
  observations,
  nparticles,
  resampling_threshold = 1,
  ref_trajectory
)

Arguments

model	a list representing a hidden Markov model, e.g. hmm_ornstein_uhlenbeck
theta	a vector of parameters as input to model functions
discretization	list containing stepsize, nsteps, statelength and obstimes
observations	a matrix of observations, of size nobservations x ydimension
nparticles	number of particles
resampling_threshold	ESS proportion below which resampling is triggered (always resample at observation times by default)
ref_trajectory	a matrix of reference trajectory, of size xdimension x statelength

Value

a matrix containing a new trajectory of size xdimension x statelength.

jeremyhengjm/UnbiasedScore documentation built on Nov. 17, 2023, 1:48 a.m.