optimise_sequential_eu: Optimise Sequential Expected Utility
In bdpopt: Optimisation of Bayesian Decision Problems

Description Usage Arguments Value Author(s) See Also

Optimise the expected utility for a sequential decision problem. The optimisation proceeds by backward induction, computing the optimal decision and corresponding expected utility at each stage over a grid for the current state summarising the posterior distribution of the unknown parameter.

1	optimise.sequential.eu(dp, mins, maxs, steps, n.sims, state.start = NA)

`dp`	A decision problem object constructed by calling `sequential.dp`.
`mins`	A numeric, atomic vector specifying the lower boundary of the grid points for each dimension of the state vector.
`maxs`	A numeric, atomic vector specifying the upper boundary of the grid points for each dimension of the state vector.
`steps`	A numeric, atomic vector specifying the step size between grid points for each dimension of the state vector.
`n.sims`	A numeric, atomic vector of length equal to `dp$n.stages` specifying the number of simulation draws to perform at each stage.
`state.start`	An optional start value for the state. If provided, this value effectively determines a fixed prior for the parameter of the decision problem (before the first stage). The first stage computations will then only be performed for this particular value. If the default value `NA` is used, computations for the first stage will be performed for all grid points, as for the subsequent stages.

If state.start equals NA, then the value returned is a list with components

`opt.decision`	Function taking a stage and a state into the optimal decision corresponding to the closest grid point at that stage.
`opt.utility`	Function taking a stage and a state into the optimal expected utility corresponding to the closest grid point at that stage.

If an explicit value for state.start is provided, the value returned is a list with components

`opt.stage1.decision`	Optimal stage 1 decision.
`opt.stage1.utility`	Optimal stage 1 utility.
`opt.decision`	Function taking a stage (greater than 1) and a state into the optimal decision corresponding to the closest grid point at that stage.
`opt.utility`	Function taking a stage (greater than 1) and a state into the optimal expected utility corresponding to the closest grid point at that stage.