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Found 4 papers, 1 papers with code
Natural Bayesian Cramér-Rao Bound with an Application to Covariance Estimation
In this paper, we propose to develop a new Cram\'er-Rao Bound (CRB) when the parameter to estimate lies in a manifold and follows a prior distribution.
The Fisher-Rao geometry of CES distributions
When dealing with a parametric statistical model, a Riemannian manifold can naturally appear by endowing the parameter space with the Fisher information metric.
Properties of a new $R$-estimator of shape matrices
This paper aims at presenting a simulative analysis of the main properties of a new $R$-estimator of shape matrices in Complex Elliptically Symmetric (CES) distributed observations.
Robust Semiparametric Efficient Estimators in Elliptical Distributions
The class of elliptical distributions can be seen as a semiparametric model where the finite-dimensional vector of interest is given by the location vector and by the (vectorized) covariance/scatter matrix, while the density generator represents an infinite-dimensional nuisance function.
