Louis Raynal

I am a Ph.D student in biostatistics at Institut Montpelliérain Alexander Grothendieck, University of Montpellier.

My thesis deals with statistical inference for intractable likelihood models and I am supervised by Jean-Michel Marin.

I am interested in Approximate Bayesian Computation (ABC), random forest, Bayesian inference, computational statistics and local methods.

Reasearch activities


PCI Logo Raynal L., Marin J.-M., Pudlo P., Ribatet M., Robert C. P., Estoup A., 2018.
ABC random forests for Bayesian parameter inference,
peer-reviewed and recommended by Peer Community In Evolutionary Biology (Blum 2017)
Bioinformatics, bty867.

Estoup A., Raynal L., Verdu P., Marin J.-M., 2018.
Model choice using Approximate Bayesian Computation and Random Forests: analyses based on model grouping to make inferences about the genetic history of Pygmy human populations,
Journal de la Société Française de Statistique.


R package abcrf (version 1.7.1, June 2018) Approximate Bayesian Computation via Random Forests

Oral presentations

February 2019, IMAG Ph.D. Students' Day, IMAG, Montpellier:
Approximate Bayesian computation and random forests.

May 2018, 50èmes Journées de Statistique, EDF Lab Paris Saclay:
Discussions around local classification and regression trees.

January 2018, Statistical Methods for Post Genomic Data (SMPGD), Montpellier:
ABC random forests for Bayesian parameter inference.

June 2017, 49èmes Journées de Statistique, Avignon:
ABC random forests for Bayesian parameter inference.

April 2017, Septièmes rencontres des jeunes statisticiens, Porquerolles:
ABC random forests for Bayesian parameter inference.

Participations to seminars

Seminar for IMAG Ph.D. students, Univ. Montpellier.