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pro vyhledávání: '"Roche, Angelina"'
We introduce a novel statistical framework for the analysis of replicated point processes that allows for the study of point pattern variability at a population level. By treating point process realizations as random measures, we adopt a functional a
Externí odkaz:
http://arxiv.org/abs/2404.19661
In this paper, we consider a functional linear regression model, where both the covariate and the response variable are functional random variables. We address the problem of optimal nonparametric estimation of the conditional expectation operator in
Externí odkaz:
http://arxiv.org/abs/2203.00518
Functional Principal Component Analysis is a reference method for dimension reduction of curve data. Its theoretical properties are now well understood in the simplified case where the sample curves are fully observed without noise. However, function
Externí odkaz:
http://arxiv.org/abs/2110.12739
A two-class mixture model, where the density of one of the components is known, is considered. We address the issue of the nonparametric adaptive estimation of the unknown probability density of the second component. We propose a randomly weighted ke
Externí odkaz:
http://arxiv.org/abs/2007.15518
Autor:
Roche, Angelina
It is more and more frequently the case in applications that the data we observe come from one or more random variables taking values in an infinite dimensional space, e.g. curves. The need to have tools adapted to the nature of these data explains t
Externí odkaz:
http://arxiv.org/abs/1903.12414
We propose an adaptive estimator for the stationary distribution of a bifurcating Markov Chain on $\mathbb R^d$. Bifurcating Markov chains (BMC for short) are a class of stochastic processes indexed by regular binary trees. A kernel estimator is prop
Externí odkaz:
http://arxiv.org/abs/1706.07034
Publikováno v:
In Journal of Statistical Planning and Inference January 2022 216:51-69
Autor:
Roche, Angelina
L'objet principal de cette thèse est de développer des estimateurs adaptatifs en statistique pour données fonctionnelles. Dans une première partie, nous nous intéressons au modèle linéaire fonctionnel et nous définissons un critère de sélec
Externí odkaz:
http://www.theses.fr/2014MON20067
Akademický článek
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Autor:
Roche, Angelina
An adaptation of Response Surface Methodology (RSM) when the covariate is of high or infinite dimensional is proposed, providing a tool for black-box optimization in this context. We combine dimension reduction techniques with classical multivariate
Externí odkaz:
http://arxiv.org/abs/1506.02886