mcmcestpars: mcmcestpars
In adbecker/tsiR: An Implementation of the TSIR Model

This function computes the set up to run the TSIR model, i.e. reconstructes susecptibles and estimates beta and alpha using MCMC computations. Used the same way as estpars.

mcmcestpars(data, xreg = "cumcases", IP = 2, regtype = "gaussian",
  sigmamax = 3, seasonality = "standard", userYhat = numeric(),
  update.iter = 10000, n.iter = 30000, n.chains = 3,
  n.adapt = 1000, burn.in = 100, sbar = NULL, alpha = NULL,
  printon = F)

`data`	The data frame containing cases and interpolated births and populations.
`xreg`	The x-axis for the regression. Options are 'cumcases' and 'cumbirths'. Defaults to 'cumcases'.
`IP`	The infectious period in weeks. Defaults to 2 weeks.
`regtype`	The type of regression used in susceptible reconstruction. Options are 'gaussian', 'lm' (linear model), 'spline' (smooth.spline with 2.5 degrees freedom), 'lowess' (with f = 2/3, iter = 1), 'loess' (degree 1), and 'user' which is just a user inputed vector. Defaults to 'gaussian' and if that fails then defaults to loess.
`sigmamax`	The inverse kernal width for the gaussian regression. Default is 3. Smaller, stochastic outbreaks tend to need a lower sigma.
`seasonality`	The type of contact to use. Options are standard for 52/IP point contact or schoolterm for just a two point on off contact or none for a single contact parameter. Defaults to standard.
`userYhat`	The inputed regression vector if regtype='user'. Defaults to NULL.
`update.iter`	Number of MCMC iterations to use in the update aspect. Default is 10000.
`n.iter`	Number of MCMC iterations to use. Default is 30000.
`n.chains`	Number of MCMC chains to use. Default is 3.
`n.adapt`	Adaptive number for MCMC. Default is 1000.
`burn.in`	Burn in number. Default is 100.
`sbar`	The mean number of susceptibles. Defaults to NULL, i.e. the function estimates sbar.
`alpha`	The mixing parameter. Defaults to NULL, i.e. the function estimates alpha.
`printon`	Whether to show diagnostic prints or not, defaults to FALSE.