Two Senses of Experimental Robustness: Result Robustness and Procedure Robustness

Event-driven and Attribute-driven Robustness

Over five decades have passed since the first wave of robust optimization studies conducted by Soyster and Falk. It is outstanding that real-life applications of robust optimization are still swept aside; there is much more potential for investigating the exact nature of uncertainties to obtain intelligent robust models. For this purpose, in this study, we investigate a more refined description...

Robustness-based portfolio optimization under epistemic uncertainty

In this paper, we propose formulations and algorithms for robust portfolio optimization under both aleatory uncertainty (i.e., natural variability) and epistemic uncertainty (i.e., imprecise probabilistic information) arising from interval data. Epistemic uncertainty is represented using two approaches: (1) moment bounding approach and (2) likelihood-based approach. This paper first proposes a ...

A Robustness Result for Sto

Robustness Aspects of Experimental Designs

1. Introduction Design of Experiments forms a fascinating branch of Statistics, which owes its origin to agricultural experiments. During 1930's to 1950's there have been major contributions from Fisher and his co-workers in the development of classical theory of design of experiments. Last five decades have witnessed a quantum jump in the development of this branch of Statistics. A careful gla...

A robustness result for stochastic control

The solution of a stochastic control problem depends on the underlying model. The actual real world model may not be known precisely and so one solves the problem for a hypothetical model, that is in general different but close to the real one; the optimal (or nearly optimal) control of the hypothetical model is then used as solution for the real problem. In this paper we assume that, what is n...