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Commit the dominance decision (sigma_nu and n) into the parameter object

Source: R/calibration_dominance.R
pm_commit_dominance.Rd

Closes calibration step 2: records the chosen sigma_nu and n, together with the scenario-I policy (beta, tau), into the pm_params object. This is the single place where step 2 mutates params.

Usage

pm_commit_dominance(
  params,
  sigma_nu,
  n,
  beta = NULL,
  tau = NULL,
  level = 0.95,
  rho = NULL
)

Arguments

params

A pm_params object with sigma_eps set.

sigma_nu, n

The chosen values (single values). Recall the calibration rule of step 2: keep the largest n whose worst-case risk still meets the ceiling, so as to spare cells of intermediate dominance (see pm_calib_dominance() and the trade-off map pm_plot_tradeoff()).

beta, tau

Scenario-I accuracy threshold and risk ceiling. Default to the dominance policy already stored in params.

level

Confidence level for the reported CI loss (default 0.95).

rho

Grid used to locate the worst case over rho. Default seq(0.001, 1, 0.001).

Value

The updated pm_params, invisibly.

Details

Requires sigma_eps to be already set (step 1), since both the scenario-I risk and the information loss depend on it. The function reports the resulting worst-case risk over rho, where that worst case occurs, and the range of the information loss – from its floor (rho -> 0, driven by sigma_eps alone) to its ceiling (rho = 1, driven by sigma_nu). A warning is raised when the worst-case risk exceeds tau: the values are still recorded, the producer being free to accept the overshoot knowingly.

Examples

para <- pm_commit_diff(pm_params())
#> Differencing step committed: beta = 0.05, tau = 0.95  ->  sigma_eps = 0.0255
#>   loss floor at rho -> 0:  E|Z| = 2.04%,  upper 95% CI = 5.00%
para <- pm_commit_dominance(para, sigma_nu = 0.3, n = 6)
#> Dominance step committed: sigma_nu = 0.3, n = 6 (beta = 0.2, sigma_eps = 0.0255107)
#>   worst-case scenario-I risk: 0.648, reached at rho = 0.901
#>   information loss E|Z| : 2.04% (rho -> 0) to 24.02% (rho = 1)
#>   information loss CI95%: 5.00% (rho -> 0) to 59.01% (rho = 1)
#>   ceiling tau = 0.9: met (margin 0.252).
para
#> <pm_params>
#>   policy
#>     dominance : beta = 0.2, tau = 0.9
#>     p%-rule   : beta = 0.1, tau = 0.9, s = 0.95
#>     diff      : beta = 0.05, tau = 0.95
#>   parameters of the mechanism
#>     sigma_nu  = 0.3
#>     sigma_eps = 0.02551067
#>     n         = 6