TRUQUET Lionel

Preprints

Debaly, M., Neumann, M.H., Truquet, L.   Mixing properties of nonstationary multivariate count processes. Link

Portier, F. Yamane, I. Truquet, L.  Scalable and hyper-parameter-free non-parametric covariate shift adaptation with  withconditional sampling. Link

Franchi, G., Truquet, L. Time series models on the simplex, with an application to dynamic modeling of relative abundance data in Ecology.Link

Truquet, L. Ergodic properties for some Markov chains models in random environments.Link

Publications

Truquet, L. Strong mixing properties of discrete-valued time series with
exogenous covariates. Link. To appear in Stochastic Processes and their Applications.

Doukhan, P., Neumann, H.M., Truquet, L. Stationarity and ergodic properties for some observation-driven models in random environments. PDF. Accepted in The Annals of Applied Probability.

Debaly, Z.M., Truquet, L. (2022) Multivariate time series models for mixed data. Link. To appear in Bernoulli.

Debaly, Zinsou Max, Truquet, L. (2021) Iterations of dependent random maps and exogeneity in nonlinear dynamics. Econometric Theory, Vol. 37, Issue 6,  pp. 1135 - 1172. PDF

Debaly, Zinsou Max, Truquet, L. (2021) A note on the stability of some Multivariate Count Autoregressions. Statistics & Probability Letters, Vol. 179, 109196. Link

Truquet, L. (2020) Coupling and perturbation techniques for categorical time series. Bernoulli 26(4): 3249-3279. PDF

Truquet, L. (2020) A perturbation analysis of some Markov chains models with time-varying parameters. Bernoulli 26(4): 2876-2906. PDF

Fokianos, K., Truquet, L. (2019) On categorical time series models with covariates.PDF.  Stochastic processes and their applications, Vol. 129, No. 9, 3446--3462.

Truquet, L. (2019) Local stationarity and time-inhomogeneous Markov chains. PDF.  The Annals of Statistics, Vol. 47, No. 4, 2023-2050. Supplementary material PDF.

Truquet, L. (2019) Root n consistent estimation of the marginal density in some stationary time series. PDF. Bernoulli, Vol. 25, No. 3, 2107-2136. Supplementary material PDF.

Truquet, L (2018) Efficient semiparametric estimation in time-varying regression models. Statistics. Vol. 52, n°3, pp. 590-618. PDF

Cadre, B., Massiot, G., Truquet, L. (2017) A nonparametric test for Cox processes.Journal of Statistical Planning and Inference. Vol. 184, pp. 48-61.PDF

Truquet, L. (2017) Parameter stability and semiparametric inference in time-varying ARCH models. Journal of Royal Statistical Society Series B, Vol. 79, pp. 1391-1414. PDF

Cadre, B., Truquet, L. (2015) Nonparametric regression estimation onto a Poisson point process covariate. ESAIM: PS, Vol. 19, pp. 251-267.

Truquet, L. (2014) On a family of contrasts for parametric inference in degenerate ARCH models. Econometric Theory, Vol. 30, Issue 6, pp. 1165-1206.

Truquet, L., Yao, Y.-F. (2012) On the quasi-likelihood estimation for random coefficient autoregressions. Statistics, Vol. 46, Issue 4, pp. 505-521.

Truquet, L. (2011) On a nonparametric resampling scheme for Markov random fields. Electron. J. Stat., Vol. 5, pp. 1503–1536.

Kachour, M., Truquet, L. (2011) A p-Order signed integer-valued autoregressive (SINAR(p)) model. Journal of Time Series Analysis, Vol. 32, Issue 3, pp. 223-236.

Truquet, L. (2010) A moment inequality of the Marcinkiewicz_Zygmund type for some weakly dependent random fields. Statistics and Probability Letters, Vol. 80, pp. 1673-1679.

Doukhan, P., Mayo, N., Truquet, L. (2009) Weak dependence, models and some applications. Metrika, Vol. 69, Numbers 2-3.

Doukhan, P., Truquet, L. (2007) A fixed point approach to model random fields. Alea, Vol. 3, pp. 111–132.

2023/2024: Asymptotic statistics and dependence (M2 course) PolyM2

2018/2019 : Cours de stat math. Cours 1, Cours 2, Cours 3

2014/2015 : Cours séries temporelles 2A. Poly, TD1.

2014/2015 : Cours statistique des processus 3A

2013/2014 : Martingales et processus de Levy. Cours+TD.

Autres supports de cours

Cours Mathématiques pour Economistes (niveau L2) PDF

Cours Probabilités pour l'ingénieur (niveau M1) PDF

Cours Statistique des processus (niveau M2) PDF