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- Yannick Baraud, Christophe Giraud, Sylvie Huet
- 2007

Let Y be a Gaussian vector whose components are independent with a common unknown variance. We consider the problem of estimating the mean µ of Y by model selection. More precisely, we start with a collection S = {Sm, m ∈ M} of linear subspaces of R n and associate to each of these the least-squares estimator of µ on Sm. Then, we use a data driven penalized… (More)

This paper explores the dynamics of attitude change in 2 dimensions (2D) as a result of social interaction. We add a rejection mechanism into the 2D bounded confidence (BC) model proposed by Deffuant et al (2001). Individuals are characterised by two-dimensional continuous attitudes, each associated with an uncertainty u, supposed constant in this first… (More)

- Yannick Baraud, Christophe Giraud, Sylvie Huet
- 2007

Let Y be a Gaussian vector whose components are independent with a common unknown variance. We consider the problem of estimating the mean µ of Y by model selection. More precisely, we start with a collection S = {Sm, m ∈ M} of linear subspaces of R n and associate to each of these the least-squares estimator of µ on Sm. Then, we use a data driven penalized… (More)

Applications on inference of biological networks have raised a strong interest in the problem of graph estimation in high-dimensional Gaussian graphical models. To handle this problem, we propose a two-stage procedure which first builds a family of candidate graphs from the data, and then selects one graph among this family according to a dedicated… (More)

The study of the interactions of cellular components is an essential base step to understand the structure and dynamics of biological networks. Various methods were recently developed for this purpose. While most of them combine different types of data and a priori knowledge, methods based on graphical Gaussian models are capable of learning the network… (More)

Proteomics relies on the separation of complex protein mixtures using bidimensional electrophoresis. This approach is largely used to detect the expression variations of proteins prepared from two or more samples. Recently, attention was drawn on the reliability of the results published in literature. Among the critical points identified were experimental… (More)

- Yannick Baraud, Sylvie Huet, Béatrice Laurent
- 2005

In this paper we propose a general methodology, based on multiple testing, for testing that the mean of a Gaussian vector in R n belongs to a convex set. We show that the test achieves its nominal level, and characterize a class of vectors over which the tests achieve a prescribed power. In the functional regression model this general methodology is applied… (More)

We propose a new opinion dynamic model based on the experiments and results of Wood et al (1996). We consider pairs of individuals discussing on two attitudinal dimensions, and we suppose that one dimension is important, the other secondary. The dynamics are mainly ruled by the level of agreement on the main dimension. If two individuals are close on the… (More)

Bootstrap methods in curve estimation have been introduced for smoothing parameter selection and for construction of conndence intervals. Most of the papers on conndence intervals use explicit bias estimation or the technique of \undersmoothing" to deal with bias. Coverage accuracy has only been considered for curve estimates with constant variance… (More)