coupled2_kernel: Runs a 2-coupled Markov kernel

In jeremyhengjm/UnbiasedScore: Unbiased estimators for partially observed diffusions

Runs a 2-coupled Markov kernel

Description

Runs two coupled kernels that leaves smoothing distribution (at each discretization level) invariant.

Usage

coupled2_kernel(
  model,
  theta,
  discretization,
  observations,
  nparticles,
  resampling_threshold = 1,
  coupled_resampling,
  ref_trajectory1,
  ref_trajectory2,
  algorithm = "CPF",
  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
algorithm	character specifying type of algorithm desired, i.e. CPF for conditional particle filter, CASPF for conditional ancestor sampling particle filter, CBSPF for conditional backward sampling particle filter
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.