Cette thèse porte sur divers aspects de lois et de processus non-gaussiens qui partagent des propriétés de changement d'échelle où intervient l'exposant 2/3. Les deux principaux objets probabilistes que nous allons présenter sont : 1) La loi de Tracy-Widom : C'est la loi limite de la plus grande valeur propre de matrices aléatoires appartenant aux beta-ensembles lorsque leur dimension tend vers l'infini. Dans un travail en commun avec Balint Virag, nous avons établi le comportement asymptotique de la queue droite de cette loi pour tout beta strictement positif, en utilisant des outils d'analyse de diffusions du type Girsanov. 2) Le ''vrai'' processus auto-répulsif (''true self repelling motion'') TSRM : C'est un processus auto-interagissant qui a été introduit par Balint Toth et Wendelin Werner. Nous nous sommes intéressés à des propriétés de cet objet liées à ses trajectoires (grandes déviations, lois du logarithme itéré) et à des calculs explicites de lois marginales (travail en collaboration avec Balint Toth). Cette étude nous a aussi amenés à aborder des questions liées à la théorie des jeux. / This thesis focuses on various aspects of non-Gaussian distributions and processes sharing scaling properties where the exponent 2/3 appears. The two probabilistic objects that we will introduce are: 1) Tracy-Widom distribution: This is the large dimensional limit of the top eigenvalue of random matrices in beta-ensembles. In a joint work with Balint Virag, we studied the asymptotic behavior of its right tail for all positive beta, using tools coming from diffusion analysis, such as the Girsanov formula. 2) The “true self repelling motion” (TSRM): This is a self-interacting process which was introduced by Balint Toth and Wendelin Werner. We have been interested in properties related to trajectories of this motion (large deviations, law of the iterated logarithm) and explicit distribution computations (joint work with Balint Toth). During this study, we have also dealt with questions related to game theory.

This thesis consists of an introduction and five papers, of which two contribute to the theory of directed random graphs and three to the theory of greedy walks on point processes.           We consider a directed random graph on a partially ordered vertex set, with an edge between any two comparable vertices present with probability p, independently of all other edges, and each edge is directed from the vertex with smaller label to the vertex with larger label. In Paper I we consider a directed random graph on ℤ2 with the vertices ordered according to the product order and we show that the limiting distribution of the centered and rescaled length of the longest path from (0,0) to (n, [na] ), a<3/14, is the Tracy-Widom distribution. In Paper II we show that, under a suitable rescaling, the closure of vertex 0 of a directed random graph on ℤ with edge probability n−1 converges in distribution to the Poisson-weighted infinite tree. Moreover, we derive limit theorems for the length of the longest path of the Poisson-weighted infinite tree.           The greedy walk is a deterministic walk on a point process that always moves from its current position to the nearest not yet visited point. Since the greedy walk on a homogeneous Poisson process on the real line, starting from 0, almost surely does not visit all points, in Paper III we find the distribution of the number of visited points on the negative half-line and the distribution of the index at which the walk achieves its minimum. In Paper IV we place homogeneous Poisson processes first on two intersecting lines and then on two parallel lines and we study whether the greedy walk visits all points of the processes. In Paper V we consider the greedy walk on an inhomogeneous Poisson process on the real line and we determine sufficient and necessary conditions on the mean measure of the process for the walk to visit all points.

This thesis presents principal components as a useful tool for data dimensio- nality reduction. In the first part, the basic terminology and theoretical properties of principal components are described and a biplot construction is derived there as well. Besides, heuristic methods for a choice of the optimum number of prin- cipal components are summarised there. Subsequently, asymptotical properties of sample eigenvalues of covariance and white Wishart matrices are described and cases of equality of some eigenvalues are distinguished at the same time. In the second part of the thesis, asymptotic distribution of the largest eigenva- lue of white Wishart matrices is described, completed with graphic illustrations. A test of the number of significant eigenvalues is suggested on the basis of this limiting distribution, and the connection of this test to the number of suitable principal components is presented. The final part of the thesis provides an over- view of advanced computational methods for the choice of an adequate number of principal components. The thesis is completed with graphical illustrations and a simulation study using Wolfram Mathematica and R.

We study Gaussian sample covariance matrices with population covariance a bounded-rank perturbation of the identity, as well as Wigner matrices with bounded-rank additive perturbations. The top eigenvalues are known to exhibit a phase transition in the large size limit: with weak perturbations they follow Tracy-Widom statistics as in the unperturbed case, while above a threshold there are outliers with independent Gaussian fluctuations. Baik, Ben Arous and Péché (2005) described the transition in the complex case and conjectured a similar picture in the real case, the latter of most relevance to high-dimensional data analysis. Resolving the conjecture, we prove that in all cases the top eigenvalues have a limit near the phase transition. Our starting point is the work of Rámirez, Rider and Virág (2006) on the general beta random matrix soft edge. For rank one perturbations, a modified tridiagonal form converges to the known random Schrödinger operator on the half-line but with a boundary condition that depends on the perturbation. For general finite-rank perturbations we develop a new band form; it converges to a limiting operator with matrix-valued potential. The low-lying eigenvalues describe the limit, jointly as the perturbation varies in a fixed subspace. Their laws are also characterized in terms of a diffusion related to Dyson's Brownian motion and in terms of a linear parabolic PDE. We offer a related heuristic for the supercritical behaviour and rigorously treat the supercritical asymptotics of the ground state of the limiting operator. In a further development, we use the PDE to make the first explicit connection between a general beta characterization and the celebrated Painlevé representations of Tracy and Widom (1993, 1996). In particular, for beta = 2,4 we give novel proofs of the latter. Finally, we report briefly on evidence suggesting that the PDE provides a stable, even efficient method for numerical evaluation of the Tracy-Widom distributions, their general beta analogues and the deformations discussed and introduced here. This thesis is based in part on work to be published jointly with Bálint Virág.

We study Gaussian sample covariance matrices with population covariance a bounded-rank perturbation of the identity, as well as Wigner matrices with bounded-rank additive perturbations. The top eigenvalues are known to exhibit a phase transition in the large size limit: with weak perturbations they follow Tracy-Widom statistics as in the unperturbed case, while above a threshold there are outliers with independent Gaussian fluctuations. Baik, Ben Arous and Péché (2005) described the transition in the complex case and conjectured a similar picture in the real case, the latter of most relevance to high-dimensional data analysis. Resolving the conjecture, we prove that in all cases the top eigenvalues have a limit near the phase transition. Our starting point is the work of Rámirez, Rider and Virág (2006) on the general beta random matrix soft edge. For rank one perturbations, a modified tridiagonal form converges to the known random Schrödinger operator on the half-line but with a boundary condition that depends on the perturbation. For general finite-rank perturbations we develop a new band form; it converges to a limiting operator with matrix-valued potential. The low-lying eigenvalues describe the limit, jointly as the perturbation varies in a fixed subspace. Their laws are also characterized in terms of a diffusion related to Dyson's Brownian motion and in terms of a linear parabolic PDE. We offer a related heuristic for the supercritical behaviour and rigorously treat the supercritical asymptotics of the ground state of the limiting operator. In a further development, we use the PDE to make the first explicit connection between a general beta characterization and the celebrated Painlevé representations of Tracy and Widom (1993, 1996). In particular, for beta = 2,4 we give novel proofs of the latter. Finally, we report briefly on evidence suggesting that the PDE provides a stable, even efficient method for numerical evaluation of the Tracy-Widom distributions, their general beta analogues and the deformations discussed and introduced here. This thesis is based in part on work to be published jointly with Bálint Virág.

The study of biological diversity has seen a tremendous growth over the past few decades. Among the commonly used indices capturing both the richness and evenness of a community, the Berger-Parker index, which relates to the maximum proportion of all species, is particularly effective. However, when the number of individuals and species grows without bound this index changes, and it is important to develop statistical tools to measure this change. In this thesis, we introduce two estimators for this maximum: the multinomial maximum and the length of the longest increasing subsequence. In both cases, the limiting distribution of the estimators, as the number of individuals and species simultaneously grows without bound, is obtained. Then, constructing the 95% confidence intervals for the maximum proportion helps improve the comparison of the Berger-Parker index among communities. Finally, we compare the two approaches by examining their associated bias corrected estimators and apply our results to environmental data.

Cette thèse porte sur divers aspects de lois et de processus non-gaussiens qui partagent des propriétés de changement d'échelle où intervient l'exposant 2/3. Les deux principaux objets probabilistes que nous allons présenter sont : 1) La loi de Tracy-Widom : C'est la loi limite de la plus grande valeur propre de matrices aléatoires appartenant aux beta-ensembles lorsque leur dimension tend vers l'infini. Dans un travail en commun avec Balint Virag, nous avons établi le comportement asymptotique de la queue droite de cette loi pour tout beta strictement positif, en utilisant des outils d'analyse de diffusions du type Girsanov. 2) Le ''vrai'' processus auto-répulsif (''true self repelling motion'') TSRM : C'est un processus auto-interagissant qui a été introduit par Balint Toth et Wendelin Werner. Nous nous sommes intéressés à des propriétés de cet objet liées à ses trajectoires (grandes déviations, lois du logarithme itéré) et à des calculs explicites de lois marginales (travail en collaboration avec Balint Toth). Cette étude nous a aussi amenés à aborder des questions liées à la théorie des jeux.