outbreaker.Rd
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() )
data | a list of named items containing input data as returned by
|
---|---|
config | a set of settings as returned by |
priors | a set of log-prior functions as returned by
|
likelihoods | a set of log-likelihood functions as returned by
|
moves | a set of movement functions as returned by
|
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.
outbreaker_data
to process input data, and
create_config
to process/set up parameters
outbreaker_data
: function to process input data
create_config
: function to create default and customise
configuration settings
custom_priors
: function to specify customised prior
functions
custom_likelihoods
: function to specify customised likelihoods
functions
custom_moves
: function to create default and customise movement
functions
Thibaut Jombart (thibautjombart@gmail.com)
## 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$w), config = list(n_iter = 2e4, sample_every = 200)) plot(out) as.data.frame(out) ## run outbreaker, no DNA sequences out2 <- outbreaker(data = list(dates = dat$onset, w_dens = w), config = list(n_iter = 2e4, sample_every = 200)) plot(out2) as.data.frame(out2) }