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Tom Rohmer

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Publications

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One-step closed-form estimator for generalized linear model with categorical explanatory variables

Alexandre Brouste , Christophe Dutang , Lilit Hovsepyan , Tom Rohmer
Statistics and Computing, 2023, 33 (6), pp.138. ⟨10.1007/s11222-023-10313-4⟩
Journal articles hal-04251559v1
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Impact of environmental disturbances on estimated genetic parameters and breeding values for growth traits in pigs

Vincent Le , Tom Rohmer , Ingrid David
Animal, 2022, 16 (4), 9 p. ⟨10.1016/j.animal.2022.100496⟩
Journal articles hal-03653106v1
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Copula miss-specification in REML multivariate genetic animal model estimation

Tom Rohmer , Anne Ricard , Ingrid David
Genetics Selection Evolution, 2022, 54 (1), pp.36. ⟨10.1186/s12711-022-00729-3⟩
Journal articles hal-03681151v1
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A Closed-form Alternative Estimator for GLM with Categorical Explanatory Variables

Alexandre Brouste , Christophe Dutang , Tom Rohmer
Communications in Statistics - Simulation and Computation, In press, pp.1-17. ⟨10.1080/03610918.2022.2076870⟩
Journal articles hal-03689206v1

A mathematical approach to deal with nanoparticle polydispersity in surface enhanced Raman spectroscopy to quantify antineoplastic agents

Antoine Dowek , Laetitia Minh Mai Lê , Tom Rohmer , François-Xavier Legrand , Hynd Remita
Talanta, 2020, 217, pp.121040. ⟨10.1016/j.talanta.2020.121040⟩
Journal articles hal-03437402v1
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A mathematical approach to deal with nanoparticle polydispersity in surface enhanced Raman spectroscopy to quantify antineoplastic agents

Antoine Dowek , Laetitia Minh Mai Lê , Tom Rohmer , François-Xavier Legrand , Hynd Remita
Talanta, 2020, 217, pp.121040. ⟨10.1016/j.talanta.2020.121040⟩
Journal articles hal-02557279v1
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Closed form Maximum Likelihood Estimator for Generalized Linear Models in the case of categorical explanatory variables: Application to insurance loss modelling

Alexandre Brouste , Christophe Dutang , Tom Rohmer
Computational Statistics, 2020, ⟨10.1007/s00180-019-00918-7⟩
Journal articles hal-01781504v3

Testing the constancy of Spearman’s rho in multivariate time series

Ivan Kojadinovic , J.-F. Quessy , Tom Rohmer
Annals of the Institute of Statistical Mathematics, 2016, 68 (5), pp.929-954. ⟨10.1007/s10463-015-0520-2⟩
Journal articles hal-01581271v1

Some results on change-point detection in cross-sectional dependence of multivariate data with changes in marginal distributions

Tom Rohmer
Statistics and Probability Letters, 2016, 119, pp.45-54. ⟨10.1016/j.spl.2016.06.026⟩
Journal articles hal-03187746v1

Detecting changes in cross-sectional dependence in multivariate time series

A. Bücher , Ivan Kojadinovic , Tom Rohmer , J. Segers
Journal of Multivariate Analysis, 2014, 132, pp.111-128. ⟨10.1016/j.jmva.2014.07.012⟩
Journal articles hal-02158618v1

UpDown – an R Package to characterize unknown disturbances from longitudinal observations

I. David , V. Le , Tom Rohmer
Book of Abstracts of the 74. Annual Meeting of the European Federation of Animal Science, INRAE, Aug 2023, Lyon, France. pp.476
Conference papers hal-04200369v1
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UpDown, une méthodologie d'identification et de caractérisation de perturbations affectant des données longitudinales

Ingrid David , Vincent Le , Tom Rohmer
54es Journées de Statistique, Université Libre de Bruxelles, Jul 2023, Bruxelles, Belgique. 5 p
Conference papers hal-04164367v1
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UpDown -an R Package to characterize unknown disturbances from longitudinal observations

Ingrid David , Vincent Le , Tom Rohmer
EAAP, Aug 2023, Lyon, France
Conference papers hal-04213268v1
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One-step closed-form estimator for generalized linear model with categorical explanatory variables

Alexandre Brouste , Christophe Dutang , Lilit Hovsepyan , Tom Rohmer
54es Journées de Statistique 2023, Université Libre de Bruxelles, Jul 2023, Bruxelles (Belgique), Belgium. 7 p
Conference papers hal-04251593v1
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Amélioration d'un outil de détection d'évènements techniques ou sanitaires à l'échelle de plusieurs bandes de truies

Gaëlle Hamelin , Tom Rohmer , Charlotte Gaillard
55. Journées de la Recherche Porcine (JRP), INRAE; Ifip, Jan 2023, Saint-Malo, France. pp.665, ⟨10.1016/j.anscip.2023.06.022⟩
Conference papers hal-04021401v1
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Impact of a non-Gaussian dependence structure on REML estimation of the bivariate genetic animal model

Tom Rohmer , Anne Ricard , Ingrid David
World Congress on Genetics Applied to Livestock Production (WCGALP 2022), Jul 2022, Rotterdam, Netherlands
Conference papers hal-03719859v1
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Impact d'une copule non-Gaussienne dans l'estimation REML du modèle génétique animal bivarié pour des populations sous sélection

Tom Rohmer , Anne Ricard , Ingrid David
Journées des Statistiques 2022, Jun 2022, Lyon, France
Conference papers hal-03699461v1

Un estimateur explicite pour le GLM à variables explicatives catégorielle

Tom Rohmer
Conférence de clôture du programme PanoRISK, Nov 2021, Le Mans, France
Conference papers hal-03681142v1

Evaluation de l’impact des perturbations sur l’estimation des paramètres et la prédiction des valeurs génétiques

Vincent Le , Tom Rohmer , Florence Ytournel , Loïc Flatres-Grall , Bruno Ligonesche
51ème JRP, Feb 2021, paris, France
Conference papers hal-03166109v1
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Assessing the impact of the non-Gaussian dependence structure in the REML estimation of the multivariate genetic model

Tom Rohmer , Anne Ricard , Ingrid David
European Mathematical Genetics Meeting, Apr 2021, Paris, France
Conference papers hal-03681137v1
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Some numerical methods with R

Tom Rohmer
Master. Université de Toulouse, France. 2023
Lectures hal-04043102v1