MATH-AmSud project FANTASTIC

statistical inFerence and sensitivity ANalysis for models described by sTochASTIC differential equations

    Members
    • Universidad de Valparaíso
      • Karine Bertin (senior)
      • Lisandro Fermin (senior)
      • Hector Olivero (senior)
      • Soledad Torres (senior)
      • Hector Araya (senior)
      • Tania Roa (junior)
    • Universidad de la República
      • Jose R. León (senior)
      • Federico Dalmao (senior)
      • Ernesto Mordecki (senior)
    • Université Grenoble Alpes / Inria Grenoble Rhône-Alpes
      • Clémentine Prieur (senior)
      • Pierre Etoré (senior)
      • Adeline Samson (senior)
      • Arthur Macherey (junior)
      • Anna Melnykova (junior)
    • Université Toulouse 3
      • Patrick Cattiaux (senior)
    • Inria Sophia Antipolis
      • Mireille Bossy (senior)
    • ENSIIE, LaMME
      • Sergio Pulido (senior)
    • Université Rennes 2
      • Nicolas Kluchnikoff (senior)
    Conferences
    • Tania Roa. 1er Workshop (virtual) de Estadística: Contribuciones de Posgrado. On consistency of least squares estimator in models sampled at random times driven by long memory noise. 08/2020.
    • Soledad Torres. Mesa de Trabajo Interdisciplinar – Modelos Predictivos covid 19 : SIR-X. 05/2020.
    • Clémentine Prieur. Numerical Analysis of Stochastic Partial Differential Equations (NASPDE) 2020, 05-06/11/2020 (reported 04-05/11/2020), Luminy (France). Goal-oriented error estimation for the reduced basis method, application to sensitivity analysis.
    Publications
    • H. Araya, N. Bahamonde, L. Fermin, T. Roa, S. Torres. On consistency of least square estimator in models sampled at random times driven by long memory noise: the Jittered case. 2020. Submitted.
    • H. Araya, N. Bahamonde, L. Fermin, T. Roa, S. Torres. On consistency of least square estimator in models sampled at random times driven by long memory noise: the Renewal case. 2020. In preparation.
    • H. Araya, N. Bahamonde, T. Roa, S. Torres. Parameter estimation for discretely observed Fractional Poisson Ornstein-Uhlenbeck Process. 2020. Submitted.
    • K. Bertin, N. Klutchnikoff, J. León and C. Prieur, Adaptive density estimation on bounded domains under mixing conditions, Electronic Journal of Statistics 14 (1), 2020.
    • K. Bertin, N. Klutchnikoff, F. Panloup and M. Varvenne, Adaptive estimation of the stationary density of a stochastic differential equation driven by a fractional Brownian motion, Statistical Inference for Stochastic Processes 23, 2020:271-300.
    • K. Bertin and N. Klutchnikoff, Adaptive regression with Brownian path covariate, 2020, Submitted.
    • K. Bertin and N. Klutchnikoff, Adaptive regression with Ornstein-Uhlenbeck covariate, 2020, In preparation.
    • M. Bossy, J. Fontbona and H. Olivero, Diffusive Limit of a system of Piecewise Deterministic Markov Processes under mean field interaction, 2020, In preparation.
    • P. Etoré, C. Prieur, D. K. Pham and L. Li, Global sensitivity analysis for models described by stochastic differential equations, Methodology and Computing in Applied Probability 22, 2020:803-831.
    • A. Melnykova, Parametric inference for hypoelliptic ergodic diffusions with full observations. Statistical Inference for Stochastic Processes 23 (3), 2020: 595-635.
    • T. Roa, S. Torres. and C. Tudor. Limit Distribution of the least squares estimator from a discrete model with observations sampled at random times and driven by standard Brownian 2020, In preparation.