In this paper we focus on robust linear optimization problems with uncertainty regions defined by ø-divergences (for example, chi-squared, Hellinger, Kullback-Leibler). We show how uncertainty regions based on ø-divergences arise in a natural way as confidence sets if the uncertain parameters...

Classical interval estimation ignores misspecification uncertainty that is almost inevitable in practice. This paper proposes an approach to construct an uncertainty interval that incorporates misspecification based on an $f$-divergence. We construct the uncertainty interval estimators using...