coarse2estim: Link coarseDataTools and EpiEstim
In EpiEstim: Estimate Time Varying Reproduction Numbers from Epidemic Curves

Description Usage Arguments Value Author(s) See Also Examples

coarse2estim Transforms outputs of coarseDataTools::dic.fit.mcmc to right format for input into estimate_R

1	coarse2estim(x = NULL, dist = x@dist, samples = x@samples, thin = 10)

`x`	An object generated by function `coarseDataTools::dic.fit.mcmc`, containing posterior estimates of the serial interval distribution.
`dist`	The parametric distribution used when estimating the serial interval. #' Should be one of "G" (Gamma), "W" (Weibull), "L" (Lognormal), "off1G" (Gamma shifted by 1), "off1W" (Weibull shifted by 1), or "off1L" (Lognormal shifted by 1). If not present, computed automatically from `x`.
`samples`	A dataframe containing the posterior samples of serial interval parameters corresponding to the parametric choice specified in `dist`. If not present, computed automatically from `x`.
`thin`	A positive integer corresponding to thinning parameter; of the posterior sample of serial interval distributions in x, only 1 in `thin` will be kept, the rest will be discarded.

A list with two elements:

si_sample: a matrix where each column gives one distribution of the serial interval to be explored, obtained from x by thinning the MCMC chain.
si_parametric_distr: the parametric distribution used when estimating the serial interval stored in x.

The Hackout3 Parameter Estimation team.

estimate_R

## 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 serial interval from data
SI.fit <- coarseDataTools::dic.fit.mcmc(dat = MockRotavirus$si_data,
                     dist = "G",
                     init.pars = init_mcmc_params(MockRotavirus$si_data, "G"),
                     burnin = 1000,
                     n.samples = 5000)

## use coarse2estim to turn this in the right format for estimate_R
si_sample <- coarse2estim(SI.fit, thin = 10)$si_sample

## use estimate_R to estimate the reproduction number
## based on these estimates of the serial interval
R_si_from_sample <- estimate_R(MockRotavirus$incidence,
                            method="si_from_sample",
                            si_sample=si_sample,
                            config = make_config(list(n2 = 50)))
plot(R_si_from_sample)

## End(Not run)