CPF_coupled_RB: Coupled Conditional Particle Filter

In pierrejacob/CoupledCPF: Coupling of Conditional Particle Filters

Description

Runs a coupled conditional particle filter, with or without ancestor sampling

Usage

CPF_coupled_RB(nparticles, model, theta, observations, ref_trajectory1,
  ref_trajectory2, coupled_resampling, with_as = FALSE,
  h = function(trajectory) {     return(trajectory) })

Arguments

nparticles	number of particles
model	a list representing a model, for instance as given by get_ar.
theta	a parameter to give to the model functions
observations	a matrix of observations of size datalength x dimension(observation)
ref_trajectory1	a first reference trajectory, of size dimension(process) x datalength
ref_trajectory2	a second reference trajectory, of size dimension(process) x datalength
coupled_resampling	a coupled resampling scheme, such as CR_indexmatching.
with_as	whether ancestor sampling should be used (TRUE/FALSE)
h	test function, which we want to integrate with respect to the smoothing distribution

Value

A list with 'new_trajectory1', 'new_trajectory2' and 'estimate1', 'estimate2'

pierrejacob/CoupledCPF documentation built on May 25, 2019, 6:05 a.m.