R library mafR
CRAN
(version 1.1.6, September 2024) Interface for Masked Autoregressive Flows
R library abcrf
GitHub
CRAN
(version 1.9, August 2022) Approximate Bayesian Computation via Random Forests
DIYABC Random Forest
(version 1.0, January 2021) Approximate Bayesian Computation via Random Forests,
for model choice and parameter inference in the context of population
genetics analysis
DIYABC
(version 2.1.0, July 2015) a user-friendly approach to Approximate
Bayesian Computation for inference on population history using molecular
markers
Marin and Robert (2014)
Bayesian Essentials with R,
Springer Texts in Statistics, Springer Verlag, New York
https://doi.org/10.1007/978-1-4614-8687-9
Marin and Robert (2007)
Bayesian Core: A Practical Approach to Computational Bayesian Statistics,
Springer Texts in Statistics, Springer Verlag, New York
https://doi.org/10.1007/978-0-387-38983-7
Rousset, Leblois, Estoup,
Marin (2024)
Better confidence intervals in simulation-based inference
biorxiv
Romero, Menichelli, Vroland,
Marin, Lèbre, Lecellier, Brehelin (2024)
Systematic analysis of the sequence features involved in the binding preferences of transcription factors
Genome Biology, 25, 187 https://doi.org/10.1186/s13059-024-03321-8 (Open Access)
Cleynen, Raynal,
Marin (2023)
Local Tree Methods for Classification: A Review and Some Dead
Ends,
Computo https://doi.org/10.57750/3j8m-8d57 (Open Access)
Pavinato, De Mita,
Marin, de Navascués (2022)
Joint inference of adaptive and demographic history from temporal population genomic data,
Peer Community Journal, 2: e78 https://doi.org/10.24072/pcjournal.203 (Open Access)
Collin, Raynal, Durif, Gautier, Vitalis, Lombaert,
Marin
and Estoup (2021)
DIYABC Random Forest v1.0 : extending approximate Bayesian computation
with supervised machine learning to infer demographic history from genetic
polymorphisms,
Molecular Ecology Resources, 21(8), 2598-2613 https://doi.org/10.1111/1755-0998.13413 (Open Access)
Chapuis, Raynal, Plantamp, Meynard, Blondin,
Marin
and Estoup (2020)
A young age of subspecific divergence in the Desert locust
Schistocerca gregaria, inferred by ABC Random Forest,
Molecular Ecology, 29(23), 4542-4558
https://doi.org/10.1111/mec.15663
Marin, Pudlo and Sedki (2019)
Consistency of Adaptive Importance Sampling and Recycling Schemes,
Bernoulli, 25(3), 1977-1998 https://doi.org/10.3150/18-BEJ1042 (Open Access)
Raynal,
Marin, Pudlo, Ribatet, Robert and Estoup (2019)
ABC random forests for Bayesian parameter inference,
Bioinformatics, 35(10), 1720-1728 https://doi.org/10.1093/bioinformatics/bty867 (Open Access)
Bessière, Taha, Petitprez, Vandel,
Marin,
Bréhélin, Lèbre and Lecellier (2018)
Probing instructions for expression regulation in gene nucleotide compositions,
PLOS Computational Biology, 14(1), e1005921 https://doi.org/10.1371/journal.pcbi.1005921 (Open Access)
Estoup, Raynal, Verdu,
Marin (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, 159(3), 167-190 Open Access numdam
Rousset and
Marin (2018)
Editorial for the Special Issue on Models and Inference in Population Genetics,
Journal de la Société Française de Statistique, 159(3), 124-125 Open Access numdam
Fraimout, Debat, Fellous, Hufbauer, Foucaud, Pudlo,
Marin,
Price, Cattel, Chen, Deprá, Duyck, Guedot, Kenis, Kimura, Loeb, Loiseau, Martinez-Sañudo,
Pascual, Polihronakis, Richmond, Shearer, Singh, Tamura, Xuéreb, Zhang and Estoup (2017)
Deciphering the Routes of invasion of Drosophila suzukii by Means of ABC Random Forest,
Molecular Biology and Evolution, 34 (4), 980–996 https://doi.org/10.1093/molbev/msx050 (Open Access)
Stoehr,
Marin and Pudlo (2016)
Hidden Gibbs random fields model selection using Block Likelihood Information Criterion,
Stat, 5(1), 158–172 https://doi.org/10.1002/sta4.112
Pudlo,
Marin, Cornuet, Estoup, Gautier and Robert (2016)
Reliable ABC model choice via random forests,
Bioinformatics, 32(6), 859-866 https://doi.org/10.1093/bioinformatics/btv684 (Open Access)
Auffray, Barbillon and
Marin (2014)
Bounding rare event probabilities in computer experiments,
Computational Statistics and Data Analysis, 80, 153-166 https://doi.org/10.1016/j.csda.2014.06.023 (Open Access)
Cornuet, Pudlo, Veyssier, Dehne-Garcia, Gautier, Leblois,
Marin and Estoup (2014)
DIYABC v2.0: a software to make Approximate Bayesian Computation inferences about population
history using Single Nucleotide Polymorphism, DNA sequence and microsatellite data,
Bioinformatics, 30(8), 1187-1189 https://doi.org/10.1093/bioinformatics/btt763 (Open Access)
Marin, Pillai, Robert and Rousseau (2014)
Relevant statistics for Bayesian model choice,
Journal of the Royal Statistical Society, Series B, 76(5), 833-859 https://doi.org/10.1111/rssb.12056 (Open Access)
Cucala and
Marin (2013)
Bayesian Inference on a Mixture Model With Spatial Dependence,
Journal of Computational and Graphical Statistics, 22(3), 584-597 https://doi.org/10.1080/10618600.2013.805652
Auffray, Barbillon and
Marin (2012)
Maximin design on non hypercube domain and kernel interpolation,
Statistics and Computing, 22(3), 703-712 https://doi.org/10.1007/s11222-011-9273-9
Besnard, Babled, Lapasset, Milhavet, Parrinello, Dantec,
Marin and Lemaitre (2012)
Unraveling cell type–specific and reprogrammable human replication origin signatures associated
with G-quadruplex consensus motifs,
Nature Structural and Molecular Biology, July 1
Celeux, El Anbari,
Marin and Robert (2012)
Regularization in regression: comparing Bayesian and frequentist methods in a poorly informative situation,
Bayesian Analysis, 7(2), 477-502 https://doi.org/10.1214/12-BA716 (Open Access)
Cornuet,
Marin, Mira and Robert (2012)
Adaptive Multiple Importance Sampling,
Scandinavian Journal of Statistics, 39(4), 798-812 https://doi.org/10.1111/j.1467-9469.2011.00756.x
Donnet and
Marin (2012)
An empirical Bayes procedure for the selection of Gaussian graphical models,
Statistics and Computing, 22(5), 1113-1123 https://doi.org/10.1007/s11222-011-9285-5
Estoup, Lombaert,
Marin, Guillemaud, Pudlo, Robert and Cornuet (2012)
Estimation of demo-genetic model probabilities with Approximate Bayesian Computation using linear discriminant analysis on summary statistics,
Molecular Ecology Resources, 12(5), 846–855 https://doi.org/10.1111/j.1755-0998.2012.03153.x
Marin, Pudlo, Robert and Ryder (2012)
Approximate Bayesian Computation methods,
Statistics and Computing, 22(6), 1167-1180 https://doi.org/10.1007/s11222-011-9288-2
Auffray, Barbillon and
Marin (2011)
Modéles réduits à partir d'expérience numériques,
Journal de la Société Française de Statistique, 152(1), 89-102 Open Access numdam
Robert, Cornuet,
Marin and Pillai (2011)
Lack of confidence in approximate Bayesian computation model choice,
Proceedings of the National Academy of Science, 108(37), 15112-15117 https://doi.org/10.1073/pnas.1102900108
Iacobucci,
Marin and Robert (2010)
On variance stabilisation by double Rao-Blackwellisation,
Computational Statistics and Data Analysis, 54, 698-710 https://doi.org/10.1016/j.csda.2008.09.020
Jouini,
Marin and Napp (2010)
Discounting and Divergence of Opinion,
Journal of Economic Theory, 145(2), 830-859 https://doi.org/10.1016/j.jet.2010.01.002
Marin and Robert (2010)
On resolving the Savage–Dickey paradox,
Electronic Journal of Statistics, 4, 643-654 https://doi.org/10.1214/10-EJS564 (Open Access)
Beaumont, Cornuet,
Marin and Robert (2009)
Adaptive approximate Bayesian computation,
Biometrika, 96(4), 983-990 https://doi.org/10.1093/biomet/asp052 (Open Access)
Casarin and
Marin (2009)
Online data processing: Comparison of Bayesian regularized particle filters,
Electronic Journal of Statistics, 3, 239-258 https://doi.org/10.1214/08-EJS256 (Open Access)
Cucala,
Marin, Robert, and Titterington (2009)
A Bayesian reassessment of nearest-neighbour classification,
Journal of the American Statistical Association, Theory and Methods, March 1, 104(485), 263-273 https://doi.org/10.1198/jasa.2009.0125
Grelaud, Robert,
Marin, Rodolphe and Taly (2009)
ABC likelihood-free methods for model choice in Gibbs random fields,
Bayesian Analysis, 4(2), 317-336 https://doi.org/10.1214/09-BA412 (Open Access)
Grelaud, Robert and
Marin (2009)
ABC methods for model choice in Gibbs random fields,
Compte Rendus Academie des Sciences - Paris, Ser. I, 347, 205–210 https://doi.org/10.1016/j.crma.2008.12.009
Ben Mansour, Jouini,
Marin, Napp and Robert (2008)
Are risk agents more optimistic? A Bayesian estimation approach,
Journal of Applied Econometrics, 23, 843-860 https://doi.org/10.1002/jae.1027
Cappé, Douc, Gullin,
Marin and Robert (2008)
Adaptive Importance Sampling in General Mixture Classes,
Statistics and Computing, 18, 447-459 https://doi.org/10.1007/s11222-008-9059-x
Cornuet, Santos, Beaumont, Robert,
Marin, Balding, Guillemaud and Estoup (2008)
Infering population history with DIY ABC: a user-friedly approach Approximate Bayesian Computation,
Bioinformatics, 24(23), 2713-2719 https://doi.org/10.1093/bioinformatics/btn514 (Open Access)
Robert and
Marin (2008)
On some difficulties with a posterior probability approximation technique,
Bayesian Analysis, 3(2), 427-442 https://doi.org/10.1214/08-BA316 (Open Access)
Consonni and
Marin (2007)
Mean field variational Bayesian inference for latent variable models,
Computational Statistics and Data Analysis, 52(2), 790-798 https://doi.org/10.1016/j.csda.2006.10.028
Douc, Guillin,
Marin and Robert (2007)
Minimum variance importance sampling via Population Monte Carlo,
ESAIM: Probability and Statistics, 11, 427-447 https://doi.org/10.1051/ps:2007028 (Open Access)
Douc, Guillin,
Marin and Robert (2007)
Convergence of adaptive mixtures of importance sampling schemes,
Annals of Statistics, 35(1), 420-448 https://doi.org/10.1214/009053606000001154 (Open Access)
Druilhet and
Marin (2007)
Invariant HPD and MAP based on Jeffreys measure,
Bayesian Analysis, 2(4), 681-692 https://doi.org/10.1214/07-BA227 (Open Access)
Kendall,
Marin and Robert (2007)
Confidence bands for Brownian motion and applications to Monte Carlo simulations,
Statistics and Computing, 17(1), 1-10 https://doi.org/10.1007/s11222-006-9001-z
Marin (2007)
Estimation of variance components for a linear Toeplitz model,
Communications in Statistics: Theory and Methods, 36(12), 2273-2288 https://doi.org/10.1080/03610920701215431
Celeux,
Marin and Robert (2006)
Iterated importance sampling in missing data problems,
Computational Statistics and Data Analysis, 50(12), 3386-3404 https://doi.org/10.1016/j.csda.2005.07.018
Celeux,
Marin and Robert (2006)
Sélection bayésienne de variables en régression linéaire,
Journal de la Sociéte Française de Statistique, 147(1), 59-79 Open Access numdam
Guillin,
Marin and Robert (2005)
Estimation bayésienne approximative par échantillonnage préférentiel,
Revue de Statistique Appliquée, LIII(1), 79-95 Open Access numdam
Cappé, Guillin,
Marin and Robert (2004)
Population Monte Carlo,
Journal of Computational and Graphical Statistics, 13(4), 907-929 https://doi.org/10.1198/106186004X12803
Marin and Dhorne (2003)
Optimal quadratic unbiased estimation for models with
linear Toeplitz covariance structure,
Statistics, 37(2), 85-99 https://doi.org/10.1080/02331880290015468
Marin and Dhorne (2002)
Linear Toeplitz covariance structure models with optimal estimators of variance components,
Linear Algebra and Its Applications, 354(1-3), 195-212
https://doi.org/10.1016/S0024-3795(02)00325-7
Celeux, Kamary, Malsiner-Walli,
Marin, Robert (2019)
Computational Solutions for Bayesian Inference in Mixture Models,
In Handbook of Mixture Analysis, chapter 5, Chapman and Hall/CRC https://doi.org/10.1201/9780429055911
Estoup, Verdu,
Marin, Robert, Dehne-Garcia, Cornuet and Pudlo (2019)
Application of approximate Bayesian computation to infer the genetic history of Pygmy
hunter-gatherers populations from Western Central Africa,
In Handbook of Approximate Bayesian Computation, chapter 18, Chapman and Hall/CRC https://doi.org/10.1201/9781315117195
Marin, Pudlo, Estoup and Robert (2019)
Likelihood-free model choice,
In Handbook of Approximate Bayesian Computation, chapter 6, Chapman and Hall/CRC https://doi.org/10.1201/9781315117195
Robert,
Marin and Rousseau (2011)
Bayesian Inference and Computation,
In Handbook of Statistical Systems Biology, chapter 3,
John Wiley & Sons https://doi.org/10.1002/9781119970606
Marin and Robert (2010)
Importance sampling methods for Bayesian discrimination between embedded models,
In Frontiers of Statistical Decision Making and Bayesian Analysis, pages 513-527, Springer-Verlag
https://doi.org/10.1007/978-1-4419-6944-6 (Open Access)
Robert and
Marin (2010)
On computational tools for Bayesian analysis,
In Rethinking Risk Measurement and Reporting, Volume I, Uncertainty, Bayesian Analysis
and Expert Judgement, chapter 2, Risk Books
Lee,
Marin, Mengersen and Robert (2009)
Bayesian inference on mixtures of distributions,
In Perspectives in Mathematical Sciences I, Probability and Statistics,
pages 165–202, World Scientific https://doi.org/10.1142/7308
Marin, Mengersen and Robert (2005)
Bayesian modelling and inference on mixtures of distributions,
In Handbook of Statistics 25, Bayesian Thinking Modeling and Computation,
pages 459-507, Elsevier https://doi.org/10.1016/S0169-7161(05)25016-2
Marin, Josse and Robert (2017)
Discussion on a paper of A. Gelman and C. Hennig: Beyond subjective and objective in statistics,
Journal of the Royal Statistical Society Series A, 180, 4 https://doi.org/10.1111/rssa.12276
Marin and Robert (2012)
Discussion on a paper of P. Fearnhead and D. Prangle: Constructing summary statistics for approximate Bayesian computation: semi-automatic approximate Bayesian computation,
Journal of the Royal Statistical Society Series B, 74, 3 https://doi.org/10.1111/j.1467-9868.2011.01010.x
Marin and Robert (2011)
Discussion on a paper of M. Girolami and B. Calderhead: Riemann manifold Langevin and Hamiltonian Monte Carlo methods,
Journal of the Royal Statistical Society Series B, 73, 2 https://doi.org/10.1111/j.1467-9868.2010.00765.x
Iaccobucci,
Marin, Robert and Mengersen (2011)
Discussion on a paper of H. Lopes, C. Carvalho, M. Johannes and N. Polson: Particle Learning for Sequential Bayesian Computation,
Bayesian Statistics 9, Oxford University Press https://doi.org/10.1093/acprof:oso/9780199694587.003.0011
Marin and Casarin and Robert (2009)
Discussion on a paper of H. Rue, S. Martino and N. Chopin: Approximate Bayesian inference for latent Gaussian models by using integrated nested Laplace approximations,
Journal of the Royal Statistical Society Series B, 71, 2 https://doi.org/10.1111/j.1467-9868.2008.00700.x
Marin and Robert (2002)
Discussion on a paper of S. L. Lauritzen and T. S. Richardson: Chain graph models and their causal interpretation,
Journal of the Royal Statistical Society Series B, 64, 3 https://doi.org/10.1111/1467-9868.00340