Ph.D. Thesis

Rohmer, T., octobre 2014, Deux tests de détection de rupture dans la copule d'observations multivariées,
Université de Pau & Université de Sherbrooke


                                                                                     Composition du jury:
                                                                                    M. Bouezmarni Taoufik, PR Univ. de Sherbrooke (co-directeur)
                                                                                    Mme Favre Anne-Catherine, PR Univ. de Grenoble (Examinatrice)
                                                                                    M. Fermanian Jean-David, PR, ENSAE (rapporteur)
                                                                                    M. Girard Stéphane, CR -HDR, INRIA (rapporteur)
                                                                                    M. Kojadinovic Ivan, PR, Univ. de Pau (co-directeur)
                                                                                    M. Quessy Jean-François, Univ de Trois-Rivières (co-directeur)

Articles (peer reviewed): [Chronological order]

    1. V. Le,T. Rohmer & I. David, Identification and characterisation of unknown disturbances in a  structured population from high-throughput phenotyping data, application to growing pig. 2024, Journal of Animal Science (pdf,HAL)

    2. A. Brouste, C. Dutang, L. Hovsepyan & T. Rohmer,  One-step closed-form estimator generalized linear model with categorigal explanatory variables, 2023. Statistics and Computing, 33(6), 138 (pdfHAL)

    3. T. Rohmer, A. Ricard & I. David, Copula miss-specification in REML multivariate genetic animal model estimation, 2022, Genetics Selection Evolution (pdfHAL

    4. A. Brouste, C. Dutang & T. Rohmer, A closed-form alternative estimator for GLM with categorical explanatory variables, 2022, Communications in Statistics,  Simulation and computation (pdf, HAL)

    5. V. Le, T. Rohmer & I. David, Impact of disturbance on the estimation of the genetic parameters and breeding values for production traits, 2022Animal. (pdf, HAL)

    6. Dowek, A.,  Minh Maï Lê, L., Rohmer, T., Legrand, F.-X., Remita,H., Lampre, I., Tfayli, A.,  Lavielle, M., Caudron, E.,  A mathematical approach to deal with nanoparticle polydispersity in surface enhanced Raman spectroscopy to quantify antineoplastic agents, Talanta, 2020, vol. 217, p. 121040 (pdf, [HAL])

    7. A. Brouste, C. Dutang & T. Rohmer, Closed form Maximum Likelihood Estimation for Generalized  Linear Models in the case of categorical explanatory variables: application to insurance loss modelling, Computational Statistics,  35, 689-724, p. 1-36 (2020) (pdfHAL)
      • R package glmtools  (dépôt logiciel, 03/2020)
  1. Rohmer, T., 2016, Some results on change-point detection in cross-sectional dependance of multivariate data with changes in marginal distributions  Statistics & Probability Letters, Volume 119, December 2016, Pages 45-54, ISSN 0167-7152. 

  2. Kojadinovic, I., Quessy, J-F. & Rohmer, T.  2015, Testing the constancy of Spearman's rho in multivariate time series, Annals of the Institute of Statistical Mathematics, Pages 1-26

  3. Bücher, A., Kojadinovic, I., Rohmer, T. & Segers, J. 2014, Detecting changes in cross-sectional dependence in multivariate time series, Journal of Multivariate Analysis, Volume 132, November 2014, Pages 111-128 

Working papers:

    1. 2018 : A. Brouste, C. Dutang,  V. Dessert, A. Matoussi & T. Rohmer , partenariat: E. Gales, P. Golhen, W. Lekeufack & B. Milleville (MMA)  Solvency tuned premium for a composite loss distribution   (2018, préprint sur HAL)

    2. 2023 : I. David,  V. Le & T. Rohmer, UpDown - an R package to identify and characterize disturbances from longitudinal observations. Article soumis [HAL]
      • R package UpDown (2022, T.Rohmer, V.Le, I.David)

    3. 2022 : T. Rohmer,  Phenotype simulation, multitrait and random regression models using Asreml.[HAL]

    4. 2023 : C. Guilmois,T. Rohmer, M. Popa-RochLearning basic mathematic skills in primary school: Testing the effectiveness of socio-constructivist and explicit instruction, Article soumis
    5. 2024 : A. Brouste, C. Dutang, L. Hovsepyan & T. Rohmer,  Fast inference in copula models with categorical explanatory variables using one-step procedures, soumission prochaine

Students :

Reviewer :

Statistics and Probability Letters (STATPRO)
International Journal of Biostatistique (IJB)
World Rabbit Congress (WRC2020)
Annal of Actuarial Sciences (AAS)
Journal of multivariate Analysis (JMVA)
Stochastic Environmental Research and Risk Assessment (SERRA)

Academic Chair:

(2019-present): Participation to the chair IDR re2a directed by Alexandre Brouste, Anis Matoussi, Mathieu Rosenbaum and Nizar Touzi