filter_for_Game: All-purpose filter
In GPGame: Solving Complex Game Problems using Gaussian Processes

Description Usage Arguments Details Value

View source: R/filter_for_Game.R

Select candidate points for conditional simulations or for criterion evaluation, based on a "window" or a probability related to the equilibrium at hand.

filter_for_Game(
  n.s.target,
  model = NULL,
  predictions = NULL,
  type = "window",
  equilibrium = "NE",
  integcontrol,
  options = NULL,
  ncores = 1,
  random = TRUE,
  include.obs = FALSE,
  min.crit = 1e-12,
  nsamp = NULL,
  Nadir = NULL,
  Shadow = NULL,
  target = NULL
)

`n.s.target`	scalar or vector of number of strategies (one value per player) to select. For `NE`, if `n.s.target` is a scalar then each player will have `round(n.s.target^(1/nobj)` strategies.
`model`	is a list of `nobj` `nobj` `km` objects
`predictions`	is a list of size `nobj`
`type`	either "`window`", "`PND`" or "`Pnash`", see details
`equilibrium`	either '`NE`', '`KSE`' or '`NKSE`' for Nash/Kalai-Smoridinsky/Nash-Kalai-Smoridinsky equilibria
`integcontrol`	is a list containing: `integ.pts`, a [`npts x dim`] matrix defining the grid, `expanded.indices` a matrix containing the indices of the integ.pts on the grid and `n.s`, a `nobj` vector containting the number of strategies per player
`options`	a list containing either the window (matrix or target) or the parameters for Pnash: method ("`simu`" or "`exact`") and `nsim`
`ncores`	`mclapply` is used if `> 1` for parallel evaluation
`random`	Boolean. If `FALSE`, the best points according to the filter criterion are chosen, otherwise the points are chosen by random sampling with weights proportional to the criterion.
`include.obs`	Boolean. If `TRUE`, the observations are included to the filtered set.
`min.crit`	Minimal value for the criterion, useful if `random = TRUE`.
`nsamp`	number of samples to estimate the probability of non-domination, useful when `type=PND` and `nobj`>3.
`Nadir, Shadow`	optional vectors of size `nobj`. Replaces the nadir or shadow point for `KSE`. If only a subset of values needs to be defined, the other coordinates can be set to `Inf` (resp. -`Inf`).
`target`	a vector of target values for the objectives to use the calibration mode

If type == "windows", points are ranked based on their distance to option$window (when it is a target vector), or based on the probability that the response belongs to option$window. The other options, "PND" (probability of non-domination, i.e., of not being dominated by the current Pareto front) and "Pnash" (probability of realizing a Nash equilibrium) base the ranking of points on the associated probability.

List with two elements: I indices selected and crit the filter metric at all candidate points

GPGame documentation built on Jan. 23, 2022, 5:06 p.m.