BIENVENUE Alexis

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Topics of productions
Affiliations
  • 1998 - 1999
    Université Claude Bernard Lyon 1
  • 2021
    Lessons learnt from the use of compartmental models over the COVID-19 induced lockdown in France.
  • 2016
    Systemic Tail Risk Distribution.
    Likelihood Inference for Multivariate Extreme Value Distributions Whose Spectral Vectors have known Conditional Distributions.
  • 1999
    Contribution to the study of random walks with memory.

  • Lessons learnt from the use of compartmental models over the COVID-19 induced lockdown in France.

    Romain GAUCHON, Nicolas PONTHUS, Catherine POTHIER, Christophe RIGOTTI, Vitaly VOLPERT, Stephane DERRODE, Jean pierre BERTOGLIO, Alexis BIENVENUE, Pierre olivier GOFFARD, Anne EYRAUD LOISEL, Simon PAGEAUD, Jean IWAZ, Stephane LOISEL, Pascal ROY
    2021
    No summary available.
    More informations See the publication

  • Systemic Tail Risk Distribution.

    Christian yann ROBERT, Alexis BIENVENUE
    Annals of Economics and Statistics | 2016
    No summary available.
    More informations

  • Likelihood Inference for Multivariate Extreme Value Distributions Whose Spectral Vectors have known Conditional Distributions.

    Alexis BIENVENUE, Christian yann ROBERT, Christian y. ROBERT
    Scandinavian Journal of Statistics | 2016
    No summary available.
    More informations See the publication

  • Contribution to the study of random walks with memory.

    Alexis BIENVENUE, Andre GOLDMAN, Andre GOLDMAN
    1999
    In this work, we study several types of walks with memory. We first study *-correlated random walks, i.e. additive functionals of a markov process on a finite state space, for which we establish an invariance theorem. We also explain a method for computing the limit covariance matrix, which we apply to the case of p-correlated markets on zd. Using the techniques of *-correlated markets on zd, we solve the recurrence/transience problem for the canonical random walk on the alternate Manhattan graph td, and we establish an invariance theorem for this walk. In the particular case of 1-correlated walks on z, we obtain a time reversal theorem as well as a result similar to the classical pitman theorem for simple walks. Then, we study the process of increasing magnitude on z by determining more particularly the law of the limit frequencies of visit of each site. Finally, we study the vertex-reinforced random walk on z, partially solving a conjecture of r. Pemantle and s. Volkov concerning the asymptotic behavior of the weights associated with the sites visited by the walk.
    More informations See the publication
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