eval_eu: Evaluate Expected Utility
In bdpopt: Optimisation of Bayesian Decision Problems

Description Usage Arguments Details Value Author(s) See Also

Simulate an estimate of the expected utility for a specific completion of the JAGS data, i.e., for a specific point in the decision space. This is a generic function for S3 objects.

1 2	eval.eu(model, utility.fun, data, n.iter, n.burn.in, n.adapt = 1000, inits = NULL, independent.SE = FALSE)

`model`	Simulation model object of class `sim.model` created using `sim.model` or `create.normal.model`.
`utility.fun`	An R function defining the utility for the decision problem. It must be possible to extract the argument names of the function supplied with `formals`, and the argument names must constitute a subset of the names used in the JAGS model specification.
`data`	A named list of R objects which, when combined with the named objects in `model$data`, leads to a complete specification of the data for the JAGS model.
`n.iter`	The number of iterations in the JAGS MCMC simulation.
`n.burn.in`	The number of burn iterations prior to the JAGS MCMC simulation.
`n.adapt`	The number of adaptation iterations prior to the burn in and JAGS MCMC simulation.
`inits`	The initial values for the chain passed on to the function `rjags::jags.model`, unless equal to its default value `NULL`, in which case JAGS chooses default initial values.
`independent.SE`	If `TRUE`, then the standard errors of the sample means used to estimate the expected utility will be computed under the assumption of i.i.d. sampling. If `FALSE`, the standard errors are instead computed using the `coda::spectrum0.ar` function.

This function is called by eval.on.grid, but also allows the user to evaluate the expected utility for a specific combination of values for the decision variables of the problem.

A list with components