activity
20052026
most citedAdaptive density estimation under dependence

14 citations · 36 across the 16 of their papers we have counts for

collaborators

17 papers

stat.ML2026

Graph-Based Correlation Matrix Generation: A Convex Optimization Approach

Ali Fakhar, K{é}vin Polisano, Ir{è}ne Gannaz +1

This work addresses the generation of theoretical correlation matrices with prescribed sparsity patterns associated to graph structures. We propose a novel convex optimization fram…

stat.ME2025

Benchmarking Brain Connectivity Graph Inference: A Novel Validation Approach

Alice Chevaux, Ali Fahkar, Kévin Polisano +2

Inferring a binary connectivity graph from resting-state fMRI data for a single subject requires making several methodological choices and assumptions that can significantly affect…

eess.SP2025

Generating Correlation Matrices with Graph Structures Using Convex Optimization

Ali Fakhar, Kévin Polisano, Irène Gannaz +1

This work deals with the generation of theoretical correlation matrices with specific sparsity patterns, associated to graph structures. We present a novel approach based on convex…

stat.AP2024

Probabilistic Models of Profiles for Voting by Evaluation

Antoine Rolland, Jean-Baptiste Aubin, Irène Gannaz +1

Considering voting rules based on evaluation inputs rather than preference rankings modifies the paradigm of probabilistic studies of voting procedures. This article proposes sever…

math.ST2021

Local Whittle estimation with (quasi-)analytic wavelets

Sophie Achard, Irène Gannaz

In the general setting of long-memory multivariate time series, the long-memory characteristics are defined by two components. The long-memory parameters describe the autocorrelati…

math.ST2021★ 1 cited

Outlier detection in multivariate functional data through a contaminated mixture model

Martial Amovin-Assagba, Irène Gannaz, Julien Jacques

In an industrial context, the activity of sensors is recorded at a high frequency. A challenge is to automatically detect abnormal measurement behavior. Considering the sensor meas…

cs.AI2021★ 1 cited

A Note on Data Simulations for Voting by Evaluation

Antoine Rolland, Jean-Baptiste Aubin, Irène Gannaz +1

Voting rules based on evaluation inputs rather than preference orders have been recently proposed, like majority judgement, range voting or approval voting. Traditionally, probabil…

stat.OT2021

Deepest Voting: a new way of electing

Jean-Baptiste Aubin, Irène Gannaz, Samuela Leoni-Aubin +1

This article aims to present a unified framework for grading-based voting processes. The idea is to represent the grades of each voter on d candidates as a point in R^d and to defi…

math.ST2020

Asymptotic normality of wavelet covariances and of multivariate wavelet Whittle estimators

Irène Gannaz

Multivariate processes with long-range dependence properties can be encountered in many fields of application. Two fundamental characteristics in such frameworks are long-range dep…

math.ST2020★ 1 cited

Asymptotic control of FWER under Gaussian assumption: application to correlation tests

Sophie Achard, Pierre Borgnat, Irène Gannaz

In many applications, hypothesis testing is based on an asymptotic distribution of statistics. The aim of this paper is to clarify and extend multiple correction procedures when th…

math.ST2018★ 2 cited

Wavelet-based and Fourier-based multivariate Whittle estimation: multiwave

Sophie Achard, Irène Gannaz

Multivariate time series with long-dependence are observed in many applications such as finance , geophysics or neuroscience. Many packages provide estimation tools for univariate…

stat.ME2017★ 5 cited

New results on approximate Hilbert pairs of wavelet filters with common factors

Sophie Achard, Irène Gannaz, Marianne Clausel +1

In this paper, we consider the design of wavelet filters based on the Thiran common-factor approach proposed in Selesnick [2001]. This approach aims at building finite impulserespo…

math.ST2014★ 1 cited

Multivariate wavelet Whittle estimation in long-range dependence

Sophie Achard, Irène Gannaz

Multivariate processes with long-range dependent properties are found in a large number of applications including finance, geophysics and neuroscience. For real data applications,…

stat.AP2014★ 1 cited

Classification of EEG recordings in auditory brain activity via a logistic functional linear regression model

Irène Gannaz

We want to analyse EEG recordings in order to investigate the phonemic categorization at a very early stage of auditory processing. This problem can be modelled by a supervised cla…

math.ST2011★ 1 cited

Wavelet penalized likelihood estimation in generalized functional models

Irène Gannaz

The paper deals with generalized functional regression. The aim is to estimate the influence of covariates on observations, drawn from an exponential distribution. The link conside…

math.ST2006★ 9 cited

Robust Estimation and Wavelet Thresholding in Partial Linear Models

Irène Gannaz

This paper is concerned with a semiparametric partially linear regression model with unknown regression coefficients, an unknown nonparametric function for the non-linear component…

math.ST2005★ 14 cited

Adaptive density estimation under dependence

Irène Gannaz, Olivier Wintenberger

Assume that is a real valued time series admitting a common marginal density with respect to Lebesgue's measure. Donoho {\it et al.} (1996) propose a near-mini…