Multiple Comparisons with the BestUsing Common Random
نویسنده
چکیده
Suppose that there are k 2 diierent systems (i.e., stochastic processes), where each system has an unknown steady-state mean performance. We consider the problem of running a single-stage simulation using common random numbers to construct simultaneous conndence intervals for i ? max j6 =i j , i = 1; 2; : : : ; k. This is known as multiple comparisons with the best (MCB). Under an assumption that the stochastic processes representing the simulation output of the different systems satisfy a functional central limit theorem, we prove that our conndence intervals are asymptotically valid (as the run lengths of the simulations of each system tends to innnity). We develop algorithms for two diierent cases: when the asymptotic covariance matrix has sphericity, and when the covariance matrix is arbitrary.
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