Abstract
Mixtures are convex combinations of laws. Despite this simple definition, a mixture can be far more subtle than its mixed components. For instance, mixing Gaussian laws may produce a potential with multiple deep wells. We study in the present work fine properties of mixtures with respect to concentration of measure and Sobolev type functional inequalities. We provide sharp Laplace bounds for Lipschitz functions in the case of generic mixtures, involving a transportation cost diameter of the mixed family. Additionally, our analysis of Sobolev type inequalities for two-component mixtures reveals natural relations with some kind of band isoperimetry and support constrained interpolation via mass transportation. We show that the Poincaré constant of a two-component mixture may remain bounded as the mixture proportion goes to 0 or 1 while the logarithmic Sobolev constant may surprisingly blow up. This counter-intuitive result is not reducible to support disconnections, and appears as a reminiscence of the variance-entropy comparison on the two-point space. As far as mixtures are concerned, the logarithmic Sobolev inequality is less stable than the Poincaré inequality and the sub-Gaussian concentration for Lipschitz functions. We illustrate our results on a gallery of concrete two-component mixtures. This work leads to many open questions. © Association des Publications de l'Institut Henri Poincaré, 2010.
Author supplied keywords
- Band isoperimetry
- Concentration of measure
- Deviation inequalities
- Finite Gaussian mixtures
- Functional inequalities
- Gaussian bounds
- Gross logarithmic Sobolev inequalities
- Mallows or Wasserstein distance
- Mass transportation
- Mixtures of distributions
- Poincaré inequalities
- Tails probabilities
- Transportation cost distances
- Transportation of measure
Cite
CITATION STYLE
Chafaï, D., & Malrieu, F. (2010). On fine properties of mixtures with respect to concentration of measure and Sobolev type inequalities. Annales de l’institut Henri Poincare (B) Probability and Statistics, 46(1), 72–96. https://doi.org/10.1214/08-AIHP309
Register to see more suggestions
Mendeley helps you to discover research relevant for your work.