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Model-based dose finding under model uncertainty using general parametric models
Model-based model uncertainty parametric models
2013/6/13
Statistical methodology for the design and analysis of clinical Phase II dose response studies, with related software implementation, are well developed for the case of a normally distributed, homosce...
The framework of this paper is that of uncertainty, that is when no reference probability measure is given. To every convex regular risk measure $\rho$ on ${\cal C}_b(\Omega)$, we associate a canonica...
Bayesian projection approaches to variable selection and exploring model uncertainty
Bayesian variable selection Kullback-Leibler projection lasso non-negative garotte preconditioning
2010/3/17
A Bayesian approach to variable selection which is based on the expected Kullback-
Leibler divergence between the full model and its projection onto a submodel has
recently been suggested in the lit...