Consistency of Sample Estimates of Risk Averse Stochastic Programs
نویسنده
چکیده
In this paper we study asymptotic consistency of law invariant convex risk measures and the corresponding risk averse stochastic programming problems for independent identically distributed data. Under mild regularity conditions we prove a Law of Large Numbers and epiconvergence of the corresponding statistical estimators. This can be applied in a straightforward way to establishing convergence w.p.1 of sample based estimators of risk averse stochastic programming problems.
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ورودعنوان ژورنال:
- J. Applied Probability
دوره 50 شماره
صفحات -
تاریخ انتشار 2013