Zobrazeno 1 - 10
of 110
pro vyhledávání: '"Fourdrinier, Dominique"'
In this paper, we consider the problem of estimating the $p\times p$ scale matrix $\Sigma$ of a multivariate linear regression model $Y=X\,\beta + \mathcal{E}\,$ when the distribution of the observed matrix $Y$ belongs to a large class of ellipticall
Externí odkaz:
http://arxiv.org/abs/2012.11920
We consider the problem of estimating the scale matrix $\Sigma$ of the additif model $Y_{p\times n} = M + \mathcal{E}$, under a theoretical decision point of view. Here, $ p $ is the number of variables, $ n$ is the number of observations, $ M $ is a
Externí odkaz:
http://arxiv.org/abs/2006.00243
We consider non parametric estimation problem for stochastic tomography regression model, i.e. we consider the estimation problem of function of multivariate variables (image) observed through its Radon transformation calculated with the random error
Externí odkaz:
http://arxiv.org/abs/1811.08814
Let $X,U,Y$ be spherically symmetric distributed having density $$\eta^{d +k/2} \, f\left(\eta(\|x-\theta|^2+ \|u\|^2 + \|y-c\theta\|^2 ) \right)\,,$$ with unknown parameters $\theta \in \mathbb{R}^d$ and $\eta>0$, and with known density $f$ and cons
Externí odkaz:
http://arxiv.org/abs/1807.04711
Publikováno v:
In Journal of Multivariate Analysis January 2021 181
Autor:
Boisbunon, Aurélie, Canu, Stephane, Fourdrinier, Dominique, Strawderman, William, Wells, Martin T.
In this article, we develop a modern perspective on Akaike's Information Criterion and Mallows' Cp for model selection. Despite the diff erences in their respective motivation, they are equivalent in the special case of Gaussian linear regression. In
Externí odkaz:
http://arxiv.org/abs/1308.2766
Publikováno v:
In Journal of Multivariate Analysis September 2019 173:18-25
Publikováno v:
Statistical Science 2012, Vol. 27, No. 1, 61-81
Let $X$ be a random vector with distribution $P_{\theta}$ where $\theta$ is an unknown parameter. When estimating $\theta$ by some estimator $\varphi(X)$ under a loss function $L(\theta,\varphi)$, classical decision theory advocates that such a decis
Externí odkaz:
http://arxiv.org/abs/1203.4989
Publikováno v:
Japanese Journal of Statistics & Data Science; Jun2024, Vol. 7 Issue 1, p329-340, 12p