Robust Bayesian analysis

300 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

Bayesian and Robust Bayesian analysis under a general class of balanced loss functions (2012, unknown): “We refer to Berger (1994) and Insua and Ruggeri (2000), among others, for useful references on robust Bayesian analysis.”
ROBUST HYPERPARAMETER ESTIMATION PROTECTS AGAINST HYPERVARIABLE GENES AND IMPROVES POWER TO DETECT DIFFERENTIAL EXPRESSION (2016, result): “It is interesting to contrast our approach with the large literature on robust Bayesian analysis (Berger, 1984, 1990; Insua and Ruggeri, 2000).”
A Review of Modern Computational Algorithms for Bayesian Optimal Design (2016, background): “Sensitivity analyses to misspeciﬁcations in the utility function have been proposed (see Rios Insua and Ruggeri [2000] for a review).”
Approximate Models and Robust Decisions (2014, background): “5 of Ruggeri et al. (2005) where the authors also consider this application).”
Reweighted Data for Robust Probabilistic Models (2016, background): “This approach leads to robust models that mitigate this speciﬁc type of mismatch (Huber, 2011; Insua and Ruggeri, 2012).”
Constructing Probability Boxes and Dempster-Shafer Structures (2003, methodology): “Robust Bayes methods acknowledge that it is sometimes very difficult to come up with precise distributions to be used as priors (Insua and Ruggeri 2000).”