Sero_Gibbs_MCMC_parameter_step: MCMC parameter step for Sero

Description Usage Arguments Value

View source: R/SERO_productspace_mcmc_functions.R

Description

MCMC parameter step for Sero

Usage

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Sero_Gibbs_MCMC_parameter_step(param, seroout, foi_const_surv, vc_agg3d,
  pop_agg3d, pop_moments_agg, dim_year, dim_age, p_at_survey, P_tot_survey,
  inc_v3d_agg, chain_cov, adapt, model_type, parameter_type, accCurrent,
  prob_Foi, posterior_distributions, ign)

Arguments

param

vector of parameters for seroprevalence

seroout

processed serology data

foi_const_surv

vector of additional foi for each survey (R0 model)

vc_agg3d

aggregated vaccination array

pop_agg3d

aggregated population array

pop_moments_agg

population moments aggregated

dim_year

years of interest

dim_age

ages of interest

p_at_survey

population proportion at time of serological survey

P_tot_survey

total population at time of serological survey

inc_v3d_agg

the incidence of vaccination (aggregated)

chain_cov

covariance of chain up to now

adapt

whether to use the chain covariance to adapt the proposal distribution is 0 or 1

model_type

either "R0" or "Foi"

parameter_type

indexing for the different types of parameters

accCurrent

current posterior probability

prob_Foi

log of the model prior for Foi model

posterior_distributions

distribution parameters for each model pseudo priors

ign

sero surveys to ignore (good for bug hunting)

Value

next step in the metropolis-within-gibbs for the parameters (param, like, prior, accept)


mrc-ide/YFestimation documentation built on Dec. 4, 2019, 4:46 p.m.