The function outbreaker is the main function of the package. It runs processes various inputs (data, configuration settings, custom priors, likelihoods and movement functions) and explores the space of plausible transmission trees of a densely sampled outbreaks.

outbreaker(data = outbreaker_data(), config = create_config(),
  priors = custom_priors(), likelihoods = custom_likelihoods(),
  moves = custom_moves())



a list of named items containing input data as returned by outbreaker_data


a set of settings as returned by create_config


a set of log-prior functions as returned by custom_priors


a set of log-likelihood functions as returned by custom_likelihoods


a set of movement functions as returned by custom_moves


The emphasis of 'outbreaker2' is on modularity, which enables customisation of priors, likelihoods and even movements of parameters and augmented data by the user. This the dedicated vignette on this topic vignette("outbreaker2_custom").


Jombart T, Cori A, Didelot X, Cauchemez S, Fraser C and Ferguson N (2014). Bayesian reconstruction of disease outbreaks by combining epidemiologic and genomic data. PLoS Computational Biology.

See also

outbreaker_data to process input data, and create_config to process/set up parameters


## get data data(fake_outbreak) dat <- fake_outbreak if (FALSE) { ## run outbreaker out <- outbreaker(data = list(dna = dat$dna, dates = dat$onset, w_dens = dat$w), config = list(n_iter = 2e4, sample_every = 200)) plot(out) ## run outbreaker, no DNA sequences out2 <- outbreaker(data = list(dates = dat$onset, w_dens = w), config = list(n_iter = 2e4, sample_every = 200)) plot(out2) }