Displaying similar documents to “Bregman superquantiles. Estimation methods and applications”

Asymptotic normality in mixture models

Sara Van De Geer (2010)

ESAIM: Probability and Statistics

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We study the estimation of a linear integral functional of a distribution F, using i.i.d. observations which density is a mixture of a family of densities k(.,y) under F. We examine the asymptotic distribution of the estimator obtained by plugging the non parametric maximum likelihood estimator (NPMLE) of F in the functional. A problem here is that usually, the NPMLE does not dominate F.
Our main aim here is to show that this can be overcome by considering a convex combination...

Asymptotic analysis of minimum volume confidence regions for location-scale families

M. Alama-Bućko, A. Zaigraev (2006)

Applicationes Mathematicae

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An asymptotic analysis, when the sample size n tends to infinity, of the optimal confidence region established in Czarnowska and Nagaev (2001) is considered. As a result, two confidence regions, both close to the optimal one when n is sufficiently large, are suggested with a mild assumption on the distribution of a location-scale family.

Confidence intervals for large non-centrality parameters

Sonia Inacio, Manuela M. Oliveira, João Tiago Mexia (2015)

Discussiones Mathematicae Probability and Statistics

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We use asymptotic linearity to derive confidence intervals for large non-centrality parameters. These results enable us to measure relevance of effects and interactions in multifactors models when we get highly statistically significant the values of F tests statistics. We show how to use our approach by considering two sets of data as application examples.