Irène Gannaz

Research

My main topics of interest are:

Multivariate time series analysis;

Non and semi parametric models;

Estimation of dependence structures;

Wavelets and applications;

Multiple testing;

Generalized regressions;

Classification of functional data.

My application field deals among others with neurosciences: functional MRI, EEG and MEG recordings.

Publications

List of publications on HAL: <link>.

Articles in journals with reviewing committee

I. Gannaz (2023). Asymptotic normality of wavelet covariances and of multivariate wavelet Whittle estimators. Stochastic Processes and their Applications, Vol 155, pp 485-534. <link> (prebublication)

M. Amovin-Assagba, I. Gannaz, J. Jacques (2022). Outlier detection in multivariate functional data through a contaminated mixture model. Computational Statistics and Data Analysis, Vol 174, pp. 107496. <link> (prépublication)

J.-B. Aubin, I. Gannaz, S. Leoni, A. Rolland (2022). Deepest Voting: a new way of electing. Mathematical Social Sciences, Vol 116, pp 1-16. <link> (prebublication)

S. Achard, M. Clausel, I. Gannaz, F. Roueff (2020). New results on approximate Hilbert pairs of wavelet filters with common factor structure. Applied and Computational Harmonic Analysis, Vol 49, N°3, pp 1025-1045. <link> (prebublication)

S. Achard, I. Gannaz (2019). Wavelet-based multivariate Whittle estimation, comparison with Fourier : multiwave. Journal of Statistical Software, Vol 69, N°6, pp 1-31. <link> [Software].

S. Achard, I. Gannaz (2016). Multivariate wavelet Whittle estimation in long-range dependence. Journal of Time Series Analysis, Vol 37, pp 476-512. <link> (prebublication).

I. Gannaz (2013). Wavelet penalized likelihood estimation in generalized functional models. TEST, Vol 22, N°1, pp 122-158. <link> (prebublication).

I. Gannaz, O. Wintenberger (2010). Adaptive density estimation under weak dependence. ESAIM: Probability and Statistics, Vol 14, pp 151-172. <link> (prebublication).

I. Gannaz (2007). Robust estimation and wavelet thresholding in partially linear models. Statistics and Computing, Vol 17, N° 4, pp 293-310. <link> (prepublication).

Conference proceedings

S. Achard, I. Gannaz, K. Polisano (2022). Génération de modèles graphiques. In GRETSI 2022. <link>

M. Amovin-Assagba, J. Jacques, I. Gannaz, F. Fossi, J. Mozul (2020). Détection d'anomalies dans des données fonctionnelles multivariées. 52èmes Journées de Statistiques de la SFdS. <link> (in french)

S. Achard, P. Borgnat, I. Gannaz, M. Roux (2019). Wavelet-based graph inference using multiple testing. In Wavelets and Sparsity XVIII (Vol. 11138, p. 1113811). International Society for Optics and Photonics. <link>

I. Gannaz, S. Achard, M. Clausel, F. Roueff (2017). Analytic wavelets for multivariate time series analysis. In Wavelets and Sparsity XVII (Vol. 10394, p. 103941X). International Society for Optics and Photonics. <link>

I. Gannaz, S. Achard, M. Clausel, F. Roueff (2017). Ondelettes analytiques, application à l’analyse des processus multivariés à longue mémoire. In GRETSI 2017.<link> (in french)

F. Millioz, I. Gannaz (2017). Estimation des paramètres d’un bruit gaussien généralisé basée sur le kurtosis des statistiques minimales. In GRETSI 2017. <link> (in french)

I. Gannaz (2014). Classification of EEG recordings in auditory brain activity via a logistic functional linear regression model. Contributions in infinite-dimensional statistics and related topics, International Workshop on Functional and Operatorial Statistics. <link> <pdf>

I. Gannaz (2012). Estimation par ondelettes dans des modèles fonctionnels généralisés. 44èmes Journées de Statistique de la SFDS. (in french)

Book chapters

S. Achard, I. Gannaz (2018) Wavelet Whittle Estimation in Multivariate Time Series Models: Application to fMRI Data. In: Bertail P., Blanke D., Cornillon PA., Matzner-Løber E. (eds) Nonparametric Statistics. ISNPS 2016. Springer Proceedings in Mathematics & Statistics, vol 250. Springer, Cham