Comparison With Standard Procedure
Kim's (2005) fully-sequential comparison with a standard procedure, used by COMPASS as the local-optimality test: the current center x* is the standard, its neighbors are the alternatives, and the procedure decides — with a controlled error probability — whether any neighbor is better than x* by more than the indifference amount delta.
Each system starts with n0 replications. For each alternative i the per-replication difference d_j = alt_i_j - standard_j (minimization, so a negative mean means the alternative is better) is accumulated into Z_i(r) = Σ d_j. A triangular continuation region with half-width a_i(r) = max(0, h² S²_i / (2δ) − (δ/2) r) brackets the walk, where S²_i is the first-stage sample variance of the differences and h² = 2 η (n0 − 1). At each stage:
Z_i(r) < −a_i(r)⇒ alternativeiis significantly better than the standard ⇒ the standard loses andiis the winner;Z_i(r) > +a_i(r)⇒ alternativeiis significantly worse ⇒ eliminatei;otherwise keep sampling
i.
When every alternative has been eliminated the standard is declared best. Bonferroni splits the error across the k alternatives: β = α / k and η = ½ ((2β)^(−2/(n0−1)) − 1) (the closed form for the single-constant case, c = 1).
This procedure requires a positive delta; with delta == 0 the boundary degenerates and the walk never terminates, which is why COMPASS uses it only when δ_L > 0 (see the ISC degraded-mode documentation).
Parameters
the overall error probability; must be in (0,1)
the indifference-zone parameter δ_L; must be positive
the first-stage sample size per system; must be at least 2
the comparison-constant flag from Kim (2005); only c = 1 is supported
a hard cap on replications per system, guaranteeing termination even if the boundary has not forced a decision; must be at least n0
Constructors
Properties
Functions
Runs the fully-sequential comparison. standard and each of the alternatives must already carry at least n0 replications. sampleOneMore is invoked to obtain one additional replication for a given point (the returned Solution is for that point with one more observation, not the merged total) — the procedure merges it internally via the supplied merge function so that callers control how accumulation happens.