Add to ORKGI give a pedagogical derivation of the Cramer-Rao Bound, which gives a lower bound on the variance of estimators used in statistical point estimation, commonly used to give numerical estimates of the systematic uncertainties in a measurement
AbstractIn this paper, we study the problem of nonparametric estimation of the mean and variance fun...
Stable distribution, also known as Lévy stable distribution, which is a rich class of heavy-tailed d...
We introduce the BLP-2LASSO model, which augments the classic BLP (Berry, Levinsohn, and Pakes, 1995...
I give a pedagogical derivation of the Cramer-Rao Bound, which gives a lower bound on the ...
summary:Bad conditioned matrix of normal equations in connection with small values of model paramete...
Chernoff bounds are a powerful application of the Markov inequality to produce strong bounds on the ...
summary:A linearization of the nonlinear regression model causes a bias in estimators of model param...
34 pages, 4 figures34 pages, 4 figures34 pages, 4 figures34 pages, 4 figuresWe study the problem of ...
Let Y be a Gaussian vector of ℝn of mean s and diagonal covariance matrix Γ. Our aim is to estimate ...
We derive sharp probability bounds on the tails of a product of symmetric non-negative random variab...
Using the pre-Grüss inequality considered by Matić-Pečarić-Ujević in a recent paper [1] and some rel...
This note shows that the asymptotic variance of Chen’s [Econometrica, 70, 4 (2002), 1683–1697] two-s...
We study an adaptive estimation procedure called the Goldenshluger–Lepski method in the context of r...
Measurement error is ubiquitous in experimental work. It leads to imperfect statistical controls, at...
International audienceThe analysis of spectra data deduced from proteomics studies in biology or inf...
AbstractIn this paper, we study the problem of nonparametric estimation of the mean and variance fun...
Stable distribution, also known as Lévy stable distribution, which is a rich class of heavy-tailed d...
We introduce the BLP-2LASSO model, which augments the classic BLP (Berry, Levinsohn, and Pakes, 1995...
I give a pedagogical derivation of the Cramer-Rao Bound, which gives a lower bound on the ...
summary:Bad conditioned matrix of normal equations in connection with small values of model paramete...
Chernoff bounds are a powerful application of the Markov inequality to produce strong bounds on the ...
summary:A linearization of the nonlinear regression model causes a bias in estimators of model param...
34 pages, 4 figures34 pages, 4 figures34 pages, 4 figures34 pages, 4 figuresWe study the problem of ...
Let Y be a Gaussian vector of ℝn of mean s and diagonal covariance matrix Γ. Our aim is to estimate ...
We derive sharp probability bounds on the tails of a product of symmetric non-negative random variab...
Using the pre-Grüss inequality considered by Matić-Pečarić-Ujević in a recent paper [1] and some rel...
This note shows that the asymptotic variance of Chen’s [Econometrica, 70, 4 (2002), 1683–1697] two-s...
We study an adaptive estimation procedure called the Goldenshluger–Lepski method in the context of r...
Measurement error is ubiquitous in experimental work. It leads to imperfect statistical controls, at...
International audienceThe analysis of spectra data deduced from proteomics studies in biology or inf...
AbstractIn this paper, we study the problem of nonparametric estimation of the mean and variance fun...
Stable distribution, also known as Lévy stable distribution, which is a rich class of heavy-tailed d...
We introduce the BLP-2LASSO model, which augments the classic BLP (Berry, Levinsohn, and Pakes, 1995...