coupled2_CPF: 2-Coupled Conditional Particle Filter

In jeremyhengjm/UnbiasedScore: Unbiased estimators for partially observed diffusions

2-Coupled Conditional Particle Filter

Description

Runs two coupled conditional particle filters (at each discretization level).

Usage

coupled2_CPF(
  model,
  theta,
  discretization,
  observations,
  nparticles,
  resampling_threshold = 1,
  coupled_resampling,
  ref_trajectory1,
  ref_trajectory2,
  treestorage = FALSE
)

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)
coupled_resampling	a 2-marginal coupled resampling scheme, such as coupled2_maximal_independent_residuals
ref_trajectory1	a matrix of first reference trajectory, of size xdimension x statelength
ref_trajectory2	a matrix of second reference trajectory, of size xdimension x statelength
treestorage	logical specifying tree storage of Jacob, Murray and Rubenthaler (2013); if missing, this function store all states and ancestors

Value

a pair of new trajectories stored as matrices of size xdimension x statelength.

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