BAYESIAN INDIFFERENCE PROCEDURES: REFINEMENTS AND EXTENSIONS

Extensions and refinements of stabilization

Self-stabilizing system is a concept of fault-tolerance in distributed computing. A distributed algorithm is self-stabilizing if, starting from an arbitrary state, it is guaranteed to converge to a legal state in a finite number of states and remains in a legal set of states thereafter. The property of self-stabilization enables a distributed algorithm to recover from a transient fault regardle...

Inferences from Indifference - Zone Selection Procedures

Two-stage indifference-zone selection procedures have been widely studied and applied. It is known that most indifference-zone selection procedures also guarantee multiple comparisons with the best confidence intervals with half-width corresponding to the indifference amount. We provide the statistical analysis of multiple comparisons with a control confidence interval that bounds the differenc...

A Bayesian Indifference Pos'i'ulate (preliminary Report)

Expected Opportunity Cost Guarantees and Indifference Zone Selection Procedures

Selection procedures help identify the best of a finite set of simulated alternatives. The indifference-zone approach focuses on the probability of correct selection, but the expected opportunity cost of a potentially incorrect decision may make more sense in business contexts. This paper provides the first selection procedure that guarantees an upper bound for the expected opportunity cost, in...

Refinements, Extensions and Generalizations of the Second Kershaw’s Double Inequality

In the paper, the second Kershaw’s double inequality concerning ratio of two gamma functions is refined, extended and generalized elegantly.