Ph.D. Thesis :

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 (pdf, HAL)
   
   
3. T. Rohmer, A. Ricard & I. David, Copula miss-specification in REML multivariate genetic animal model estimation, 2022, Genetics Selection Evolution (pdf, HAL) 
   
   
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, 2022, Animal. (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) (pdf, HAL)
   
   • R package glmtools  (dépôt logiciel, 03/2020)

8. 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. 
   
   • Supplementary material here -Monte Carlo simulations and specific situation under strong-mixing condition-
   • R package npopTest (2016, T.Rohmer, màj 2018)
   
   
9. 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
   
   
10. 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:

11. 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)
    
    
    
12. 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)
    
    
13. 2022 : T. Rohmer,  Phenotype simulation, multitrait and random regression models using Asreml.[HAL]
    
    
14. 2023 : C. Guilmois,T. Rohmer, M. Popa-Roch,  Learning basic mathematic skills in primary school: Testing the effectiveness of socio-constructivist and explicit instruction, Article soumis

15. 2024 : A. Brouste, C. Dutang, L. Hovsepyan & T. Rohmer,  Fast inference in copula models with categorical explanatory variables using one-step procedures, soumission prochaine

    
    
    

• 2019-2022, Vincent Le, ph.d. student in genetic statistics, thesis co-supervised with Ingrid David (Inrae GenPhySE). "Nouvelle mesure de la robustesse des animaux d'élevage par utilisation des données de phénotypage haut-débits" https://hal.inrae.fr/tel-03967884
  
  
• 2022, Gaelle Hamelin, stage M2, co-supervised with  Charlotte Gaillard (Inrae, PEGASE). "Amélioration  d'un outil de détection d'évenements (techniques ou sanitaires) à l'échelle de plusieurs bande de truies". abstract JRP here
  
  
• 2021-2024, Lilit Hovsepyan, ph.d. student in Asymptotic statistic and stochastic process,  thesis co-supervised with Alexandre Brouste and Irene Votsi
  
• 2024, Victoria Bruning, stage M2 co-supuervisé avec Estelle Kuhn (Inrae, Maiage)
  
• 2024, Amandine Rouillard, stage M2 co-supuervisé avec Charlotte Gaillard et Anne Boudon (Inrae, PEGASE)