o2geosocial (version 1.1.3)

custom_priors: Customise priors for outbreaker

Description

Priors can be specified in several ways in o2geosocial (see details and examples). The most flexible way to specify a prior is to provide a prior function directly. This function must take an argument 'param', which is a list which contains all the states of the parameters and augmented data. See the documentation of create_param for more information.

Usage

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

Value

A named list of custom functions with class custom_priors. Values set to NULL will be ignored and default functions will be used instead.

Arguments

...

A list or a series of named, comma-separated functions implementing priors. Each function must have a single argument, which corresponds to a 'outbreaker_param' list.

x

an outbreaker_config object as returned by create_config.

Author

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

Details

There are three ways a user can specify priors:

1) Default: this is what happens when the 'config' has default values of prior parameters.
2) Customized parameters: in this case, the prior functions are the default ones from the package, but will use custom parameters, specified by the user through create_config.

3) Customized functions: in this case, prior functions themselves are specified by the user, through the '...' argument of 'custom_priors'. The requirements is that such functions must have either hard-coded parameters or enclosed values. They will take a single argument which is a list containing all model parameters with the class 'outbreaker_param'. ALL PRIORS functions are expected to return values on a LOG SCALE.

Priors currently used for the model are:

• pi (reporting probability): default function is a beta distribution implemented in cpp_prior_pi. New prior functions should use x$pi to refer to the current value of pi, assuming their argument is called x.

• a (first spatial parameter (population)): default function is a uniform distribution implemented in cpp_prior_a. New prior functions should use x$a to refer to the current value of a, assuming their argument is called x.

• b (second spatial parameter (distance)): default function is a uniform distribution implemented in cpp_prior_b. New prior functions should use x$b to refer to the current value of b, assuming their argument is called x.

Examples

## SPECIFYING PRIOR PARAMETERS
## Default values: pi follows a beta distribution (parameters 10, 1), 
## a and b follow a uniform distribution (parameters 0, 5)
default_config <- create_config()
## Use the variables prior_a, prior_b and prior_pi to change the parameters
## of the prior distributions can be 
new_config <- create_config(prior_a = c(0,5), prior_b = c(0,5),
                        prior_pi = c(2, 1))


## SPECIFYING A NEW PRIOR FUNCTION
## Example: flat prior for pi between 0.5 and 1
f <- function(x) {ifelse(x$pi > 0.5, log(2), log(0))}
priors <- custom_priors(pi = f)
## test the new prior distribution
priors$pi(list(pi=1))
priors$pi(list(pi=.6))
priors$pi(list(pi=.2))
priors$pi(list(pi=.49))