The Principle of Strong Diminishing Transfer

We reconsider the principles of diminishing transfer (introduced by Kolm [1976]) and dual diminishing transfer (introduced by Mehran [1976]). It appears that if a Rank Dependent Expected Utility (RDEU) maximizer respects the principle of diminishing (resp. dual diminishing) transfer, then he behaves in accordance with the Expected Utility model (resp. Yaari's dual model).This leads us to define the principle of strong diminishing transfer, which is a combination of the principles of diminishing and dual diminishing transfer. We give necessary conditions for a RDEU maximizer to respect this principle.These results are applied to the problem of inequality measurement.Inequality Measurement, Principle of Diminishing Transfers

Regular updating

We study the Full Bayesian Updating rule for convex capacities. Following a route suggested by Jaffray (1992), we define some properties one may want to impose on the updating process, and identify the classes of (convex and strictly positive) capacities that satisfy these properties for the Full Bayesian updating rule.

The Principle of Strong Diminishing Transfer

International audienceWe reconsider the principles of diminishing transfer (introduced by Kolm [1976]) and dual diminishing transfer (introduced by Mehran [1976]). It appears that if a Rank Dependent Expected Utility (RDEU) maximizer respects the principle of diminishing (resp. dual diminishing) transfer, then he behaves in accordance with the Expected Utility model (resp. Yaari's dual model).This leads us to define the principle of strong diminishing transfer, which is a combination of the principles of diminishing and dual diminishing transfer. We give necessary conditions for a RDEU maximizer to respect this principle.These results are applied to the problem of inequality measurement

Robust output feedback sampling control based on second order sliding mode

International audienceThis paper proposes a new second order sliding mode output feedback controller. This latter is developped in the case of finite sampling frequency and is using only output information in order to ensure desired trajectory tracking with high accuracy in a finite time in spite of uncertainties and perturbations. This new strategy is evaluated in simulations on an academic example