Two-stage selection procedures have been widely studied and applied in determining the required sample size (i.e., the number of replications or batches) for selecting the best of...
We consider how to efficiently allocate computing resources in order to infer the best of a finite set of simulated systems, where best means that the system has the maximal expec...
This paper develops procedures for selecting a set of normal populations with unknown means and unknown variances in order that the final subset of selected populations satisfies ...
We consider the general, widely applicable problem of selecting from n real-valued random variables a subset of size m of those with the highest means, based on as few samples as ...
Background: Causal networks based on the vector autoregressive (VAR) process are a promising statistical tool for modeling regulatory interactions in a cell. However, learning the...