Let Xn, . . . , X1 be i.i.d. random variables with distribution function F and finite expectation. A statistician, knowing F , observes the X values sequentially and is given two chances to choose X’s using stopping rules. The statistician’s goal is to select a value of X as large as possible. Let V 2 n equal the expectation of the larger of the two values chosen by the statistician when procee...

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Statistical selection procedures are used to select the best of a finite set of alternatives, where “best” is defined in terms of each alternative’s unknown expected value, and the expected values are inferred through statistical sampling. One effective approach, which is based on a Bayesian probability model for the unknown mean performance of each alternative, allocates samples based on maxim...

Cost-effectiveness analysis (CEA) represents the most important tool in the health economics literature to quantify and qualify the reasoning behind the optimal decision process in terms of the allocation of resources to a given health intervention. However, the practical application of CEA in regulatory process is often limited by some critical barriers, and decisions in clinical practice are ...

A main focus in economics is on binary choice situations, in which human agents have to choose between two alternative options. The classical view is that decision making consists of valuating each option, comparing the two expected values, and selecting the higher one. Some neural correlates of option values have been described in animals, but little is known about how they are represented in ...

We propose a sample average approximation (SAA) method for stochastic programming problems involving an expected value constraint. Such problems arise, for example, in portfolio selection with constraints on conditional value-at-risk (CVaR). Our contributions include an analysis of the convergence rate and a statistical validation scheme for the proposed SAA method. Computational results using ...

There has been an increasing interest in using expected value of information (EVI) theory in medical decision making, to identify the need for further research to reduce uncertainty in decision and as a tool for sensitivity analysis. Expected value of sample information (EVSI) has been proposed for determination of optimum sample size and allocation rates in randomized clinical trials. This art...

In this contribution we discuss a stochastic framework for air traffic conflict resolution. The conflict resolution task is posed as the problem of optimizing an expected value criterion. Optimization is carried out by Monte Carlo Markov Chain (MCMC) simulation. A numerical example illustrates the proposed strategy. Copyright c © 2005 IFAC

The attraction effect shows that adding a third alternative to a choice set can alter preference between the original two options. For over 30 years, this simple demonstration of context dependence has been taken as strong evidence against a class of parsimonious value-maximising models that evaluate alternatives independently from one another. Significantly, however, in previous demonstrations...

Decision makers within a jurisdiction facing evidence of positive but uncertain incremental net benefit of a new health care intervention have viable options where no further evidence is anticipated to:(1)adopt the new intervention without further evidence;(2)adopt the new intervention and undertake a trial; or(3)delay the decision and undertake a trial.Value of information methods have been sh...