o2geosocial (version 1.1.2)

custom_likelihoods: Customise likelihood functions for o2geosocial

Description

This function is used to specify customised likelihood functions for o2geosocial 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:

Usage

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

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.

Arguments

...

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

x

an outbreaker_config object as returned by create_config.

Author

Initial version by Thibaut Jombart, rewritten by Alexis Robert ()

Details

• 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.

• space: the likelihood of spatial distances; by default, the function cpp_ll_space is used.

• age: the likelihood of the age contacts; by default, the function cpp_ll_age 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

Examples

## specify a null model by disabling all likelihood components
f_null <- function(data, config = NULL, param, i) {
  return(0.0)
}


null_model <- custom_likelihoods(timing_sampling = f_null,
                                 timing_infections = f_null,
                                 reporting = f_null,
                                 space = f_null,
                                 age = f_null)

null_config <- list(find_import = FALSE,
                    n_iter = 200, gamma = 100, delta = 30,
                    sample_every = 1)

## load data
data("toy_outbreak_short")
dt_cases <- toy_outbreak_short$cases
dt_cases <- dt_cases[order(dt_cases$Date), ][1:15,]
dt_regions <- toy_outbreak_short$dt_regions
all_dist <- geosphere::distGeo(matrix(c(rep(dt_regions$long, nrow(dt_regions)), 
                                        rep(dt_regions$lat, nrow(dt_regions))), 
                                      ncol = 2), 
                               matrix(c(rep(dt_regions$long, each = nrow(dt_regions)), 
                                        rep(dt_regions$lat, each = nrow(dt_regions))),
                                      ncol = 2))

dist_mat <- matrix(all_dist/1000, nrow = nrow(dt_regions))
pop_vect <- dt_regions$population
names(pop_vect) <- rownames(dist_mat) <- colnames(dist_mat) <- dt_regions$region

data <- outbreaker_data(dates = dt_cases$Date, age_group = dt_cases$age_group,
                        region = dt_cases$Cens_tract, population = pop_vect, 
                        distance = dist_mat)

res_null <- outbreaker(data = data,
                       config = null_config,
                       likelihoods = null_model)