Adapt the look-ahead horizon depending on the replicate allocation or a target ratio
horizon(
model,
current_horizon = NULL,
previous_ratio = NULL,
target = NULL,
Wijs = NULL
)randomly selected horizon for next iteration (adpative) if no target is provided,
otherwise returns the update horizon value.
hetGP or homGP model
horizon used for the previous iteration, see details
ratio before adding the previous new design
scalar in ]0,1] for desired n/N
optional previously computed matrix of Wijs, see Wij
If target is provided, along with previous_ratio and current_horizon:
the horizon is increased by one if more replicates are needed but a new ppint has been added at the previous iteration,
the horizon is decreased by one if new points are needed but a replicate has been added at the previous iteration,
otherwise it is unchanged.
If no target is provided, allocate_mult is used to obtain the best allocation of the existing replicates,
then the new horizon is sampled from the difference between the actual allocation and the best one, bounded below by 0.
See (Binois et al. 2017).
M. Binois, J. Huang, R. B. Gramacy, M. Ludkovski (2019),
Replication or exploration? Sequential design for stochastic simulation experiments,
Technometrics, 61(1), 7-23.
Preprint available on arXiv:1710.03206.