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PR <= alpha or CR <= beta, and rounding
the sample size up could not repair it. The search is now refined by
solving the two binding risk equations (Nelder-Mead in log coordinates),
the sample size is rounded up from the binding solution, and both risks
are verified at the delivered size. Known-theta sample sizes are now the
minimal feasible integers, e.g. the reported moisture case (PRQ = 0.005,
CRQ = 0.01, USL = 0.05, theta = 500) changes from n = 112 (violating
both risks) to n = 117. If the refinement does not converge, the
constrained-search solution is delivered after verification, with a
warning.PR and
CR, the OC curve and the plots now describe the delivered
integer plan, and n equals sample_size.
Unknown-theta plans keep the previous reporting semantics.accProb() no longer fails for a Beta plan with
acceptability constant k = 0 (floating-point cancellation made the
closed-form discriminant marginally negative)."gk_adjustment".These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.