ISMCMC: Independence Sampler/RWM MCMC

In JMacDonaldPhD/REpi: Pseudo-Marginal Analysis of partially observed Epidemics

Independence Sampler/RWM MCMC

Description

Generates dependent samples from target distribution using a Independence Sampler/RWM MCMC proposal scheme.

Usage

ISMCMC(
  init,
  U_init,
  epiModel,
  obsFrame,
  epiSample,
  I0,
  alpha,
  logPrior,
  lambda,
  V,
  S,
  noIts
)

Arguments

init	initial value of epidemic parameters
U_init	initial value of random variables used to construct epidemic trajectory.
epiModel	epidemic model
obsFrame	Generator function for observational model.
epiSample	Observed epidemic data.
I0	Initial state of the epidemic, which assumed to be known.
alpha	Observational parameters to be passed on to the log-likelihood function generated by obsFrame(X_sim)
logPrior	Functions which calculate log-density of the assumed priors of the epidemic parameters.
lambda	Random Walk Metropolis (RWM) proposal scale parameter.
V	A square matrix containing the covariance values for RWM proposal. Shape of matrix should match the length of the init parameter.
S	Number of non-centered random variables to be 'refreshed' in Independence Sampler proposal step.
noIts	Number of iterations of MCMC sampler scheme to carry out.

Value

A matrix of MCMC samples and proposal acceptance rate of the sample.

JMacDonaldPhD/REpi documentation built on Aug. 2, 2022, 2:09 p.m.