This function is used to specify customised likelihood functions for outbreaker. Custom functions are specified as a named list or series of comma-separated, named arguments, indicating which log-likelihood component they compute. Values currently available are:

custom_likelihoods(...)

# S3 method for custom_likelihoods
print(x, ...)

Arguments

...

a named list of functions, each computing a log-likelihood component.

x

an outbreaker_config object as returned by create_config.

Value

A named list of functions with the class custom_likelihood, each implementing a customised log-likelihood components of outbreaker. Functions which are not customised will result in a NULL component.

a list of named functions

Details

  • genetic: the genetic likelihood; by default, the function cpp_ll_genetic is used.

  • timing_sampling: the likelihood of sampling times; by default, the function cpp_ll_timing_sampling is used.

  • timing_infections: the likelihood of infection times; by default, the function cpp_ll_timing_infections is used.

  • reporting: the likelihood of the reporting process; by default, the function cpp_ll_reporting is used.

  • contact: the likelihood of the contact tracing data; by default, the function cpp_ll_contact is used.

All log-likelihood functions should have the following arguments, in this order:

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

  • param: a list of parameters with the class create_param

See also

See customization vignette for detailed examples on how to customize likelihoods.

Examples

## specify a null model by disabling all likelihood components f_null <- function(data, param) { return(0.0) } null_model <- custom_likelihoods(genetic = f_null, timing_sampling = f_null, timing_infections = f_null, reporting = f_null, contact = f_null) null_config <- list(find_import = FALSE, n_iter = 200, sample_every = 1) ## load data x <- fake_outbreak data <- outbreaker_data(dates = x$sample, dna = x$dna, w_dens = x$w) res_null <- outbreaker(data = data, config = null_config, likelihoods = null_model) ## visualise ancestries to see if all transmission trees have been explored plot(res_null, type = "alpha")