make_mcmc_control Creates a list of mcmc control parameters to be used in
config is an argument of the
estimate_R function. This is used to configure the MCMC chain used to
estimate the serial interval within
estimate_R (with method
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A positive integer giving the burnin used in the MCMC when estimating the serial interval distribution.
A positive integer corresponding to thinning parameter; the MCMC
will be run for
An integer used as the seed for the random number generator at the start of the MCMC estimation; useful to get reproducible results.
vector of size 2 corresponding to the initial values of parameters to use for the SI distribution. This is the shape and scale for all but the lognormal distribution, for which it is the meanlog and sdlog.
si_data, should be a dataframe with 5
EL: the lower bound of the symptom onset date of the infector (given as an integer)
ER: the upper bound of the symptom onset date of the infector (given as an integer). Should be such that ER>=EL
SL: the lower bound of the symptom onset date of the infected individual (given as an integer)
SR: the upper bound of the symptom onset date of the infected individual (given as an integer). Should be such that SR>=SL
type (optional): can have entries 0, 1, or 2, corresponding to doubly interval-censored, single interval-censored or exact observations, respectively, see Reich et al. Statist. Med. 2009. If not specified, this will be automatically computed from the dates
Assuming a given parametric distribution for the serial interval distribution
the posterior distribution of the serial interval is estimated directly fom
these data using MCMC methods implemented in the package
An object of class
estimate_R_mcmc_control with components
burnin, thin, seed, init_pars. This can be
used as an argument of function
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## Not run: ## Note the following examples use an MCMC routine ## to estimate the serial interval distribution from data, ## so they may take a few minutes to run ## load data on rotavirus data("MockRotavirus") ## estimate the reproduction number (method "si_from_data") mcmc_seed <- 1 burnin <- 1000 thin <- 10 mcmc_control <- make_mcmc_control(burnin = burnin, thin = thin, seed = mcmc_seed) incid <- MockRotavirus$incidence method <- "si_from_data" overall_seed <- 2 config <- make_config(incid = incid, method = method, si_parametric_distr = "G", mcmc_control = mcmc_control, n1 = 500 n2 = 50, seed = overall_seed) R_si_from_data <- estimate_R(incid, method = method, si_data = MockRotavirus$si_data, config = config) ## End(Not run)
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