adaptiveSISfsMCMC: Adaptive fsMCMC MCMC for SIS Epidemic Panel Data

In JMacDonaldPhD/Epidemics: Inference For Epidemics (one line, title case)

Description

Adapts proposal parameters for with a view of optimal of a target using forward simulation MCMC scheme.

Usage

adaptiveSISfsMCMC(
  obsTransData,
  I_0,
  obsTimes,
  N,
  beta0,
  gamma0,
  thetaLim,
  lambda0,
  V0,
  delta,
  noDraws,
  s,
  noIts,
  burnIn = 0,
  lagMax = NA,
  thinningFactor = 1
)

Arguments

obsTransData	Interpanel transition data.
I_0	Initial number of infectives in the population.
obsTimes	Times at which epidemic cohort were followed up.
N	Population size.
beta0	Starting value for infectious process parameter.
gamma0	Starting value for removal/recovery process parameter.
lambda0	Starting value for RWM proposal parameter which is to be adapted.
V0	Starting state for RWM proposal Covariance matrix which is to be adapted.
delta	Probability that a proposal is made based on the starting proposal conditions.
noDraws	Number of underlying variables to be drawn (i.e max. number of events in observation period)
s	Number of underlying random variables of the process to refresh.
noIts	Number of MCMC iterations.
lagMax	Plotting parameter for acf() function.
thinningFactor	Controls the factor by which MCMC samples are thinned, to reduce dependency.

Value

Proposal parameters which can be used for more optimal exploration of target distribution (plus MCMC summary).

See Also

Other Panel Data MCMC: SIR_fsMCMC_blockedIS(), adaptiveSIR_PseudoMarginalMCMC(), adaptiveSIS_PseudoMarginalMCMC()

JMacDonaldPhD/Epidemics documentation built on Jan. 10, 2020, 2:48 a.m.