Vice Chairman of the Statistics Department

Chairman of the Statistical Engineering and data Science Dpt of the Institut de Statistique de l'Université de Paris (ISUP-UPMC)

Michel.broniatowski@upmc.fr

Experience

PhD Mathematics 1981, Université Paris 6 (Pierre et Marie Curie)

Doctorat d'Etat Mathematics 1987, Université Paris 6 (Pierre et Marie Curie)

Assistant Professor Université de Reims 1981-1987

Associate Professor Université Paris 6 (Pierre et Marie Curie) 1987-1988

Professor Université de Strasbourg 1988-1993

Professor Université de Reims 1994-2003

Professor Université Paris 6 (Pierre et Marie Curie) since 2004

Teaching

Numerical Probability

Statistical modelling

Limit Theorems in Mathematical Statistics

Choice of models, robustness

Extreme values

Invited Professor in

University of Padova (Italy)

Hebrew University Jerusalem (Israel)

University Yale (USA)

Indiana State University Bloomington (USA)

Madison University (USA)

Charles University (Prague, Czech Republic)

Univ Federico II Naples (Italy)

Delaware University (USA)

KUL (Leuven, Belgium)

University of Roma I (Italy)

FAU University (Erlangen, Germany)

ULB (Brussels, Belgium)

etc

Research topics

Statistical Inference through divergences and duality

Extreme values

Large deviations and Statistics

Algorithms

Optimal designs

Editorial activities

Associate Editor Annales de l’ISUP since 2000

Associate Editor Modélisation stochastique avancée et statistique (Stochastic Modeling and Statistics,), since 2016

Referee for many journals in Statistics and Probability

IEEE Inf Th, JMVA, JSPI, Stat Comp, Ann IHP, Bernoulli, Stat and Prob Letters, Studi Math Hungarica, etc

Expert for grant qualifications (Italy, European grants, Denmark) ; expert for scientific evaluation of Mathematical department (Ecole Normale Supérieure Cachan)

Expertise in extreme risks (Official french governmental Committee following Fukushima accident, expertise extreme risks and nuclear plant safety)

Award: Lambda-Mu Or 2009

Publications

BOOKS

Celant, Giorgio; Broniatowski, Michel Interpolation and extrapolation optimal designs. 2.General finite dimensional linear models. Mathematics and Statistics Series. ISTE, London; John Wiley & Sons, Inc., Hoboken, NJ, 2017 316p  ISBN: 978-1-78630-054-6

Celant, Giorgio; Broniatowski, Michel Interpolation and extrapolation optimal designs. 1. Polynomial regression and approximation theory. Mathematics and Statistics Series. ISTE, London; John Wiley & Sons, Inc., Hoboken, NJ, 2016. xxvi+254 pp. ISBN: 978-1-84821-995-3

M Broniatowski, G Celant. Inferenza statistica, corso di Statistica per la Laurea. Ed Cleup, Padova, 2000

PAPERS

EXTREME VALUES (Statistics,  Probability, asymptotic analysis)

Biret, Maëva; Broniatowski, Michel; Cao, Zansheng Gibbs Principle under extreme conditions; Under revision Probability and Mathematical Statistics, 2017

Biret, Maëva; Broniatowski, Michel; Cao, Zansheng

Broniatowski, Michel, Cao, Zhansheng Light tails: all summands are large when the empirical mean is large. Extremes 17 (2014), no. 2, 305–336.

Broniatowski, Michel; Depire, Alexandre; Ritov, Ya'acov Bivariate Cox models. Mathematical methods in survival analysis, reliability and quality of life, 93–107, Appl. Stoch. Methods Ser., ISTE, London, 2008.

Barbe Ph, Broniatowski, M . Blowing number of a distribution for a statistics and loyal estimators. Statist. Probab. Lett. 69 (2004), no. 4, 465–475.

Broniatowski, Michel Comment. Metron 61 (2003), no. 2, 181–184.

Broniatowski, M  From extreme values to large deviations, Theory of  Probability and their Applications, 44,1, 164-165, 1999

Broniatowski, M.; Weber, M. Strong laws for sums of extreme values. Teor. Veroyatnost. i Primenen. 42 (1997), no. 3, 553--563; reprinted in Theory Probab. Appl. 42 (1997), no. 3, 395–404 (1998)

Broniatowski, Michel; Fuchs, Aimé Tauberian theorems, Chernoff inequality, and the tail behavior of finite convolutions of distribution functions. Adv. Math. 116 (1995), no. 1, 12–33.

Beirlant, Jan; Broniatowski, Michel; Teugels, Jozef L.; Vynckier, Petra The mean residual life function at great age: applications to tail estimation. Extreme value theory and applications (Villeneuve d'Ascq, 1992). J. Statist. Plann. Inference 45 (1995), no. 1-2, 21–48.

Broniatowski, Michel On the estimation of the Weibull tail coefficient. J. Statist. Plann. Inference 35 (1993), no. 3, 349–365.

Broniatowski, Michel; Fuchs, Aimé Comportement comparé de la loi des moyennes et des minimums de v.a. indépendantes équidistribuées. (French) [Laws of random variables whose mean and minimum behavior are similar] C. R. Acad. Sci. Paris Sér. I Math. 310 (1990), no. 6, 415–417.

Broniatowski, Michel; Weber, Michel Lois fortes des grands nombres pour des sommes de valeurs extrêmes. (French) [Strong laws of large numbers for sums of extreme values] C. R. Acad. Sci. Paris Sér. I Math. 309 (1989), no. 6, 367–370.

Broniatowski, Michel; Deheuvels, Paul; Devroye, Luc On the relationship between stability of extreme order statistics and convergence of the maximum likelihood kernel density estimate. Ann. Statist. 17 (1989), no. 3, 1070–1086.

Broniatowski, Michel Convergence for the sample extremes via convolutions. Mathematical statistics and probability theory, Vol. A (Bad Tatzmannsdorf, 1986), 43–52, Reidel, Dordrecht, 1987.

Broniatowski, Michel Grandes, très grandes et petites déviations pour des suites de variables aléatoires réelles indépendantes. (French) [Large, very large and small deviations for sequences of independent identically distributed real random variables] C. R. Acad. Sci. Paris Sér. I Math. 305 (1987), no. 13, 627–630.

DIVERGENCES (Statistics and Analysis)

Broniatowski, Michel; Stummer, Wolfgang Some universal insights on divergences for statistics, machine learning and artificial intelligence. Geometric structures of information, 149–211, Signals Commun. Technol., Springer, Cham, 2019. 62B10 (62B99 94A17)

Broniatowski, Michel. A weighted bootstrap procedure for divergence minimization problems ; to appear in Analytical Methods in Statistics Springer, Cham, 2017

Broniatowski, Michel; Decurninge, Alexis Estimation for models defined by conditions on their L-moments. IEEE Trans. Inform. Theory 62 (2016), no. 9, 5181–5198.

Broniatowski, Michel Minimum divergence estimators, maximum likelihood and exponential families. Statist. Probab. Lett. 93 (2014), 27–33.

Broniatowski, Michel Weighted sampling, maximum likelihood and minimum divergence estimators. Geometric science of information, 467–478, Lecture Notes in Comput. Sci., 8085, Springer, Heidelberg,

Broniatowski, Michel; Vajda, Igor Divergences in parametric setting without smoothing or grouping. Rend. Circ. Mat. Palermo (2) Suppl. No. 84 (2012), 91–106

Broniatowski, Michel; Vajda, Igor Several applications of divergence criteria in continuous families. Kybernetika (Prague) 48 (2012), no. 4, 600–636. 62B10 (62F10 62F35)

Broniatowski, Michel; Toma, Aida; Vajda, Igor Decomposable pseudodistances and applications in statistical estimation. J. Statist. Plann. Inference 142 (2012), no. 9, 2574–2585.

Broniatowski, Michel; Keziou, Amor Divergences and duality for estimation and test under moment condition models. J. Statist. Plann. Inference 142 (2012), no. 9, 2554–2573.

Toma, Aida; Broniatowski, Michel Dual divergence estimators and tests: robustness results. J. Multivariate Anal. 102 (2011), no. 1, 20–36.

Broniatowski, Michel; Keziou, Amor Parametric estimation and tests through divergences and the duality technique. J. Multivariate Anal. 100 (2009), no. 1, 16–36.

Broniatowski, M.; Leorato, S. An estimation method for the Neyman chi-square divergence with application to test of hypotheses. J. Multivariate Anal. 97 (2006), no. 6, 1409–1436.

Broniatowski, Michel; Keziou, Amor Minimization of ϕ-divergences on sets of signed measures. Studia Sci. Math. Hungar. 43 (2006), no. 4, 403–442.

Broniatowski, Michel A minimax result for divergence projections on locally convex sets of measures. Rend. Circ. Mat. Palermo (2) Suppl. No. 77 (2006), 69–79.

Broniatowski, M. Estimation of the Kullback-Leibler divergence. Math. Methods Statist. 12 (2003), no. 4, 391–409 (2004).

Barbe, Ph Broniatowski, M Simulation in exponential families   Transactions ACM , Modelling and Simulation , 9,3, 203-223, 1999

LARGE DEVIATIONS AND STATISTICS

Broniatowski, Michel; Caron, Virgile Long runs under a conditional limit distribution. Ann. Appl. Probab. 24 (2014), no. 6, 2246–2296.

Broniatowski, Michel; Caron, Virgile Small variance estimators for rare event probabilities. ACM Trans. Model. Comput. Simul. 23 (2013), no. 1, Art. 7, 23 pp.

Broniatowski, Michel ;Caron, Virgile Conditional Inference in Parametric Models Chapter 9, p125-146 in Statistical Models and Methods for Reliability and Survival Analysis, Vincent Couallier (Editor), Leo Gerville-Reache (Editor), Catherine Huber-Carol (Editor), Nikolaos Limnios (Editor), Mounir Mesbah (Editor) ISBN: 978-1-84821-619-8 , 2013 Wiley Ed, London

Barbe, Ph.; Broniatowski, M. On sharp large deviations for sums of random vectors and multidimensional Laplace approximation. Teor. Veroyatn. Primen. 49 (2004), no. 4, 743--774; reprinted in Theory Probab. Appl. 49 (2005), no. 4, 561–588.

Barbe, Ph.; Broniatowski, M. Large-deviation probability and the local dimension of sets. Proceedings of the 19th Seminar on Stability Problems for Stochastic Models, Part I (Vologda, 1998). J. Math. Sci. (New York) 99 (2000), no. 3, 1225–1233.

Broniatowski, Michel; Tallay, Samir Simulation de lois conjuguées et application à l'estimation de la transformée de Cramér dans Rd. (French) [Simulation in conjugate distributions with application to the estimation of the Cramér transform in Rd] C. R. Acad. Sci. Paris Sér. I Math. 328 (1999), no. 6, 531–534.

Barbe, Philippe; Broniatowski, Michel Note on functional large deviation principle for fractional ARIMA processes. Stat. Inference Stoch. Process. 1 (1998), no. 1, 17–27.

Barbe, Ph.; Broniatowski, M. Large deviation principle for sequential rank processes. Math. Methods Statist. 7 (1998), no. 1, 98–110.

Broniatowski, M.; Weber, M. Strong laws for sums of extreme values. Teor. Veroyatnost. i Primenen. 42 (1997), no. 3, 553--563; reprinted in Theory Probab. Appl. 42 (1997), no. 3, 395–404 (1998).

Barbe, P.; Broniatowski, M. Deviation principle for set indexed processes with independent increments. Studia Sci. Math. Hungar. 33 (1997), no. 4, 393–418.

Barbe, Ph.; Broniatowski, M. Functional Erdős-Rényi laws for processes indexed by sets. Proceedings of the XVII Seminar on Stability Problems for Stochastic Models, Part II (Kazanʹ, 1995). J. Math. Sci. 83 (1997), no. 3, 356–359.

Broniatowski, Michel; Mason, David M. Extended large deviations. J. Theoret. Probab. 7 (1994), no. 3, 647–666.

Broniatowski, Michel Grandes, très grandes et petites déviations pour des suites de variables aléatoires réelles indépendantes. (French) [Large, very large and small deviations for sequences of independent identically distributed real random variables] C. R. Acad. Sci. Paris Sér. I Math. 305 (1987), no. 13, 627–630.

OPTIMAL DESIGNS

Celant, Giorgio; Broniatowski, Michel Interpolation and extrapolation optimal designs. 2.General finite dimensional linear models. Mathematics and Statistics Series. ISTE, London; John Wiley & Sons, Inc., Hoboken, NJ, 2017 300p  to appear.

Celant, Giorgio; Broniatowski, Michel Interpolation and extrapolation optimal designs. 1. Polynomial regression and approximation theory. Mathematics and Statistics Series. ISTE, London; John Wiley & Sons, Inc., Hoboken, NJ, 2016. xxvi+254 pp. ISBN: 978-1-84821-995-3

Broniatowski, Michel; Celant, Giorgio Optimal extrapolation design for the Chebyshev regression. Ann. I.S.U.P. 59 (2015), no. 3, 3–22. 62K05

Broniatowski, Michel; Celant, Giorgio Some overview on unbiased interpolation and extrapolation designs. Ann. I.S.U.P. 58 (2014), no. 3, 27–60. 62K05

Broniatowski, Michel; Celant, Giorgio; Di Battista, Marco; Leoni-Aubin, Samuela Upper bounds for the error in some interpolation and extrapolation designs. Comm. Statist. Theory Methods 41 (2012), no. 16-17, 3002–3019.

Broniatowski, M.; Celant, G. Optimality and bias of some interpolation and extrapolation designs. J. Statist. Plann. Inference 137 (2007), no. 3, 858–868.

ALGORITHMS

Al Mohamad D and Broniatowski M:  A two-step proximal-point algorithm for the calculus of divergence-based estimators in finite mixture models; The Canadian Journal of Statistics/La revue canadienne de statistique To appear 2019

Biret M, Broniatowski M Safip, a streaming algorithm for inverse problems. Submitted, 2016

Diaa Al Mohamad, Michel Broniatowski. Two Proximal point EM algorithms with applications to mixture models. Under Revision  IEEE Inf Theory 2017

Diaa Al Mohamad, Michel Broniatowski. A Proximal Point Algorithm for Minimum Divergence Estimators with Application to Mixture Models Entropy, MDPI, 2016, 18 (8), pp.277.

Al Mohamad, Diaa; Broniatowski, Michel Generalized EM algorithms for minimum divergence estimation. Geometric science of information, 417–426, Lecture Notes in Comput. Sci., 9389, Springer, Cham, 2015.

 Broniatowski, Michel; Diebolt, Jean Loi stationnaire et loi des fluctuations pour le processus autorégressif général d'ordre un. (French) [Stationary distribution and innovations in the first-order general autoregressive process] C. R. Acad. Sci. Paris Sér. I Math. 305 (1987), no. 5, 203–206.

Broniatowski, M.; Celeux, G.; Diebolt, J. Reconnaissance de mélanges de densités par un algorithme d'apprentissage probabiliste. (French) [Recognition of density mixtures by a probabilistic learning algorithm] Data analysis and informatics, III (Versailles, 1983), 359–373, North-Holland, Amsterdam, 1984.

Broniatowski, Michel; Diebolt, Jean Sur l'ergodicité et la stabilité d'une chaîne à accroissements indépendants exponentiels. (French) [The ergodicity and stability of an independent exponentially growing chain] C. R. Acad. Sci. Paris Sér. I Math. 298 (1984), no. 13, 301–304.

VARIOUS CONTRIBUTIONS IN STATISTICS 

Broniatowski, M., Jurečková, J., Moses, A. K., & Miranda, E. (2019). Composite Tests under Corrupted Data. Entropy, 21(1), 63.

Broniatowski, Michel, Jana Jurečková, and Jan Kalina. "Likelihood ratio testing under measurement errors." Entropy 20.12 (2018): 966.

Atlagh, M.; Broniatowski, M.; Celant, G. A convergence result for a class of asymptotically linear estimators. Comm. Statist. Theory Methods 41 (2012), no. 16-17, 2922–2931.

Broniatowski, Michel; Mignot, Pascal A self-adaptive technique for the estimation of the multifractal spectrum. Statist. Probab. Lett. 54 (2001), no. 2, 125–135.

Broniatowski, Michel Cross-validation methods in kernel nonparametric density estimation: a survey. Publ. Inst. Statist. Univ. Paris 37 (1993), no. 3-4, 3–28.

Broniatowski, Michel Convergence L1 presque sûre de l'estimateur de la densité obtenu par validation croisée. (French) [L1-consistent cross-validated density estimation] C. R. Acad. Sci. Paris Sér. I Math. 303 (1986), no. 10, 487–490.

Mohamed Achibi, ,Michel Broniatowski,Catherine Duveau,Alice Marboeuf

. Bivariate Cox models and copulas Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability October 2012 226: 476-487.

APPLIED STATISTICS

Division cellulaire dans le méristème plan du Tropaellum pelregrinum I, 1982, CRAS, avec C. Fuchs et  A. Raftery

 Division cellulaire dans le méristème plan du Tropaellum pelregrinum I I, 1982, CRAS, avec C. Fuchs et A. Raftery

 Division cellulaire et onde mitotique,1983, avec C.Fuchs et A. Raftery, Revue de Cytologie Végétale.

 Une étude économétrique de l' inflation sectorielle; modélisation non paramétrique . Avec G. Kebabdjian, revue de l' ISMEA, 1985.

 Modèle keynésien de la dynamique des prix. Avec G. Kebabdjian. Colloque Keynes aujourd'hui, Economica, 1985.

 Application des mélanges de lois de probabilité à la reconnaissance des régimes de trafic routier; avec F.Couthon et M. Danech-Pajouh. Revue des Transports et de leur Sécurité, 1996.

 K. Chamaillard^,,E. Huguet^c, M. Broniatowski^d Stokes vector for small rough particles: Regression analysis, Journal of Quantitative Spectroscopy and Radiative Transfer , Volume 101, Issue 3, October 2006, Pages 512–521

Ph-D STUDENTS

• Samira JAHOURI (1990). Max-sum Model for energy storage .
• Sylviane WEY-RACADOT (1991). Testing the number of modes ; Large deviation and Kullback-Leibler divergence estimation.
• Arezki MIHOUBI (1994). Bootstrap and non parametric density estimation .
• Philippe BARBE (1993). Bootstrap. Spacings .
• Samir TALLAY (1995). Moderate deviations ; simulation in exponential families.
• Ouagnina HILLI (1995). Minimum Hellinger distance estimators in non linear time series .
• Pascal MIGNOT (2000). Multifractal spectrum estimation.

• Karine CHAMAILLARD (2001). Optical properties of interstellar grains, an inverse problem in Statistics.

• Samantha LEORATO (2002). Minimum Chi-square estimators, duality approach .

• Amor KEZIOU (2003). Estimation and tests by minimum divergence approach

• Fateh CHEBANA (2003). Weighted Bickel-Rosenblatt tests .

• Alexandre DEPIRE (2005). Models of dependence, estimation in hidden Markov chains with a context. Bruxelles.
• Samuela LEONI-AUBIN (2005). Estimation and tests in semi parametric models .

• Omar EL-DAKKAK. (2008) Sequential empirical measure ; Stein estimators.

• Jacques TOUBOUL (2010). Projection pursuit and divergences.
• Mohamed CHERFI (2010) Semi parametrics and selection criterions.

• Mohamed ACHIBI (2012) Multivariate Cox models and quantile regression ; applications to industrial statistics..

• Virgile CARON (2012) Conditioned random walks, Importance Sampling and conditional inference.

• Zangshen CAO (2012) Weighted bootstrap, random walk, conditioning under extreme events.

• Alexis DECURNINGE Detection, muyltivariate quantiles and optimal transportation.

• Boris BERANGER Max Stable processes and applications (joint supervision with Pr Sisson, UNSW, Sidney).

• Maeva BIRET 2016 Robust planning, inverse problems.

• Assia BOUMAHDAF Queues in Air trafic regulation ; inferential aspects.

• Matthieu CLERTANT Joint supervision with Pr J O'Quigley 2016 , UPMC Paris. Semi-parametric Bayesian model, applications in dose finding studies.

• Diaa AL MOHAMAD 2016 Proximal algorithms, semi parametric mixtures and Phi divergences.

• D RABENORO (joint supervision with Pr P Deheuvels , UPMC Paris). Limit conditional Theorems ; Large deviations for compound renewal processes.

Under supervision:

• E MIRANDA: Optimal designs for high level quantile estimation.

• T TOUATI: Sanov type results for the weighted empirical measures with applications to Statistics.

• P BERTRAND: Conditions de Monge, transport optimal et pont relationnel, co-tutelle avec J.F. Marcotorchino