Add to ORKGA generalized Cramér-Rao analogue for median-unbiased estimators having continuous joint density functions is given by defining a dispersion measure, joint diffusivity, analogous to the generalized variance in mean-unbiased estimation and extending the usual definition of median-unbiasedness to the multivariate case. The resulting inequality is valid for multivariate distributions with a vector parameter.median-unbiased estimation Cramer-Rao diffusivity
In this letter, we consider Cramér-Rao bounds (CRBs) on the variance of unbiased vector parameter es...
International audienceWe consider the optimal performance of blind separation of Gaussian sources. I...
International audienceWe consider the optimal performance of blind separation of Gaussian sources. I...
AbstractA generalized Cramér-Rao analogue for median-unbiased estimators having continuous joint den...
In mean-unbiased estimation we normally prefer an estimator, in the class of mean-unbiased estimator...
Adopting a measure of dispersion proposed by Alamo [1964], and extending the analysis in Stangenhaus...
The paper considers a family of probability distributions depending on a parameter. The goal is to d...
This paper aims at providing a fresh look at semiparametric estimation theory and, in particular, at...
This paper aims at providing a fresh look at semiparametric estimation theory and, in particular, at...
International audienceWe begin with two possible extensions of Stam's inequality and of de Bruijn's ...
Abstract—An important aspect of estimation theory is char-acterizing the best achievable performance...
International audienceIn the present work, we show how the generalized Cramér-Rao inequality for the...
International audienceThis paper deals with Cramér-Rao inequalities in the context of nonextensive s...
The paper considers a family of probability distributions depending on a parameter. The goal is to d...
In this letter, we consider Cramér-Rao bounds (CRBs) on the variance of unbiased vector parameter es...
In this letter, we consider Cramér-Rao bounds (CRBs) on the variance of unbiased vector parameter es...
International audienceWe consider the optimal performance of blind separation of Gaussian sources. I...
International audienceWe consider the optimal performance of blind separation of Gaussian sources. I...
AbstractA generalized Cramér-Rao analogue for median-unbiased estimators having continuous joint den...
In mean-unbiased estimation we normally prefer an estimator, in the class of mean-unbiased estimator...
Adopting a measure of dispersion proposed by Alamo [1964], and extending the analysis in Stangenhaus...
The paper considers a family of probability distributions depending on a parameter. The goal is to d...
This paper aims at providing a fresh look at semiparametric estimation theory and, in particular, at...
This paper aims at providing a fresh look at semiparametric estimation theory and, in particular, at...
International audienceWe begin with two possible extensions of Stam's inequality and of de Bruijn's ...
Abstract—An important aspect of estimation theory is char-acterizing the best achievable performance...
International audienceIn the present work, we show how the generalized Cramér-Rao inequality for the...
International audienceThis paper deals with Cramér-Rao inequalities in the context of nonextensive s...
The paper considers a family of probability distributions depending on a parameter. The goal is to d...
In this letter, we consider Cramér-Rao bounds (CRBs) on the variance of unbiased vector parameter es...
In this letter, we consider Cramér-Rao bounds (CRBs) on the variance of unbiased vector parameter es...
International audienceWe consider the optimal performance of blind separation of Gaussian sources. I...
International audienceWe consider the optimal performance of blind separation of Gaussian sources. I...