• Statistique des processus : stabilité, racines unitaires, coefficients aléatoires, diffusions, comportement asymptotique, déviations.
• Approches bayésiennes : domaine chronologique, modèles linaires dynamiques, modèles graphiques, statistique en grande dimension, spike-and-slab.
• Probabilités et statistiques appliquées : sciences du vivant.

Testing for the extent of instability in nearly unstable processes. M. Badreau, F. Proïa. Journal of Time Series Analysis. 2024. Voir
Consistency and asymptotic normality in a class of nearly unstable processes. M. Badreau, F. Proïa. Statistical Inference for Stochastic Processes. Vol. 26, pp 619-641, 2023. Voir
A Bayesian approach for partial Gaussian graphical models with sparsity. E. Okome Obiang, P. Jézéquel, F. Proïa. Bayesian Analysis. Vol. 18, pp 465-490, 2023. Voir
A partial graphical model with a structural prior on the direct links between predictors and responses. E. Okome Obiang, P. Jézéquel, F. Proïa. ESAIM: Probability and Statistics. Vol. 25, pp 298-324, 2021. Voir
Comments on the presence of serial correlation in the random coefficients of an autoregressive process. F. Proïa, M. Soltane. Statistics & Probability Letters. Vol. 170, pp 1-9, 2021. Voir
Moderate deviations in a class of stable but nearly unstable processes. F. Proïa. Journal of Statistical Planning and Inference. Vol. 208, pp 66-81, 2020. Voir
Probabilistic reconstruction of genealogies for polyploid plant species. F. Proïa, F. Panloup, C. Trabelsi, J. Clotault. Journal of Theoretical Biology. Vol. 462, pp 537-551, 2019. Voir
On the Bickel-Rosenblatt test of goodness-of-fit for the residuals of autoregressive processes. A. Lagnoux, T.M.N. Nguyen, F. Proïa. ESAIM: Probability and Statistics. Vol. 23, pp 464-491, 2019. Voir
A test of correlation in the random coefficients of an autoregressive process. F. Proïa, M. Soltane. Mathematical Methods of Statistics. Vol. 27, pp 119-144, 2018. Voir
Testing for residual correlation of any order in the autoregressive process. F. Proïa. Communications in Statistics – Theory and Methods. Vol. 47, pp 628-654, 2018. Voir
Stationarity against integration in the autoregressive process with polynomial trend. F. Proïa. Probability and Mathematical Statistics. Vol. 38, pp 1-26, 2018. Voir
On the characterization of flowering curves using Gaussian mixture models. F. Proïa, A. Pernet, T. Thouroude, G. Michel, J. Clotault. Journal of Theoretical Biology. Vol. 402, pp 75-88, 2016. Voir
On Ornstein-Uhlenbeck driven by Ornstein-Uhlenbeck processes. B. Bercu, F. Proïa, N. Savy. Statistics & Probability Letters. Vol. 85, pp 36-44, 2014. Voir
Moderate deviations of functional of Markov processes. V. Bitseki Penda, H. Djellout, L. Dumaz, F. Merlevède, F. Proïa. ESAIM: Proceedings. Vol. 44, pp 214-238, 2014. Voir
Moderate deviations for the Durbin-Watson statistic related to the first-order autoregressive process. V. Bitseki Penda, H. Djellout, F. Proïa. ESAIM: Probability and Statistics. Vol. 18, pp 308-331, 2014. Voir
A SARIMAX coupled modelling applied to individual load curves intraday forecasting. S. Bercu, F. Proïa. Journal of Applied Statistics. Vol. 40, pp 1333-1348, 2013. Voir
Further results on the H-Test of Durbin for stable autoregressive processes. F. Proïa. Journal of Multivariate Analysis. Vol. 118, pp 77-101, 2013. Voir
A sharp analysis on the asymptotic behavior of the Durbin-Watson statistic for the first-order autoregressive process. B. Bercu, F. Proïa. ESAIM: Probability and Statistics. Vol. 17, pp 500-530, 2013. Voir

GitHub : https://github.com/FredericProia/

HDR : https://hal.univ-angers.fr/UNIV-ANGERS-THESE/tel-03715444v1
Autorégressifs à coefficients variables – Modèles graphiques partiels – Applications aux sciences du vivant.
Soutenue le 05/07/2022 à l’Université d’Angers.

Thèse : http://www.theses.fr/2013BOR14877
Autocorrélation et stationnarité dans le processus autorégressif.
Soutenue le 04/11/2013 à l’Université de Bordeaux.
Direction : Bernard Bercu, Université de Bordeaux.