- Echantillonnage
- Estimation de variance
- Données Manquantes
- Méthodes de rééchantillonnage
- Résultats asymptotiques
Campus de Ker Lann
51 Rue Blaise Pascal
BP 37203
35172 BRUZ Cedex
Je suis Attaché Principal de l'Insee (promotion 2000 de l'Ensai)
Je suis membre de l'IRMAR (UMR CNRS 6625)
J'ai obtenu mon doctorat en Statistique auprès de l'Université de Rennes 2
Titre : Méthodes de Bootstrap en population finie (manuscrit)
Soutenu le 14 décembre 2007
J'ai obtenu mon Habilitation à Diriger des Recherches auprès de l'Université de Rennes 1
Titre : Some contributions to Sampling and Estimation in Surveys (manuscrit et présentation)
Soutenue le 28 novembre 2014
Curriculum vitae en français (format pdf)
Chapitres de livres
Chauvet G. (2020) Introduction to Sampling Techniques. In: Ros F., Guillaume S. (eds) Sampling Techniques for Supervised or Unsupervised Tasks, Springer, Cham, pp. 1-21.
Publié ou Accepté
[40] T-H. Vo, G. Chauvet, A. Happe, E. Oger, S. Paquelet, V. Garès (2023), An extension of Fellegi-Sunter probabilistic record linkage model for mixed-type data with application to the French national health data system. A paraître dans Computational Statistics and Data Analysis.
[39] O. Bouriaud, P. Brion, G. Chauvet (2023), An extension of the weight share method when using a continuous sampling frame. A paraître dans Survey Methodology.
[38] Z. Chupeau, F. Mercier, E. Rouxel, B. Le Bot, G. Chauvet, T. Siméon, N. Bonvallot, C. Zaros, C. Chevrier, P. Glorennec (2022), Pre- and post-natal exposure of children to organophosphate flame retardants: A nationwide survey in France. Environment International, 168.
[37] G. Chauvet (2022), A cautionary note on the Hanurav-Vijayan sampling algorithm. Journal of Survey Statistics and Methodology.
[36] M-A. Metten, N. Costet, J-F. Viel, G. Chauvet (2022), Inverse probability weighting to handle attrition in cohort studies: some guidance and a call for caution. BMC Medical Research methodology, 22(45).
[35] V. Garès, G. Chauvet, D. Hajage (2022), Variance estimators for weighted and stratified linear dose-response function estimators using generalized propensity score. Biomedical Journal, 64(1), pp. 33-56.
[34] G. Chauvet, C. Goga (2022), Asymptotic efficiency of the calibration estimator in a high-dimensional data setting. Journal of Statistical Planning and Inference, 217, pp. 177-187.
[33] P. Bessonneau, G. Brilhault, G. Chauvet, C. Garcia (2021). With-replacement bootstrap variance estimation for household surveys: principles, examples and implementation. Survey Methodology, 47(2), pp. 313-347.
[32] L. Daniel, M. Michot, M. Esvan, P. Guérin, G. Chauvet, F. Pelé (2020), Perceptions, knowledge and practices regarding indoor environmental pollution: a quantitative study among adults of childbearing age. International journal of Environment Research and Public Health, 17(20), p. 7669.
[31] G. Chauvet (2021). A note on Chromy's sampling procedure. Journal of Survey Statistics and Methodology, 9(5), pp. 1050-1061.
[30] G. Chauvet, A.A. Vallée (2020), Consistency of estimators and variance estimators in two-stage sampling. Journal of the Royal Statistical Society, Series B, vol 82, n° 3, pp. 797-815.
[29] G. Chauvet (2020). Large sample properties of the Midzuno sampling scheme with probabilities proportional to size. Statistics and Probability Letters, vol 159.
[28] G. Chauvet, R. Le Gleut (2020), Inference under pivotal sampling: properties, variance estimation and application to tesselation for spatial sampling. Scandinavian Journal of Statistics, pp. 1-24. [Présentation]
[27] B. Gelein, G. Chauvet (2020). Preserving the distribution function in surveys in case of imputation for zero inflated data. Journal of Statistical Planning and Inference, vol n° 206, pp. 84-99.
[26] L. Belin, G. Chauvet, Y. De Rycke, D. Hajage, F. Tubach (2018), Closed-form variance estimator for weighted propensity score estimators with survival outcome. Biometrical Journal, vol n° 60(6), pp. 1151-1163.
[25] H. Chaput, G. Chauvet, D. Haziza, L. Salembier, J. Solard (2018), Joint imputation procedures for categorical variables with application to the French Wealth Survey. Statistics and Applications, vol. 16, pp.123-144 (Invited paper for a special issue in honor of the 80th birthday of Professor J.N.K. Rao) [Présentation]
[24] G. Chauvet, W. Do Paco (2018), Exact balanced random imputation for sample survey data. Computational Statistics and Data Analysis.Computational Statistics and Data Analysis, vol n° 118(C), pp. 1-16.
[23] H. Juillard, G. Chauvet (2018), Variance estimation under monotone non-response for a panel survey. Survey Methodology, vol. 44(2), pp. 269-289.
[22] G. Chauvet, C. Goga (2018), Gini coefficient and Gini coefficient change: linearization versus Bootstrap to estimate the variance. Survey Methodology, vol. 44(1), pp. 17-42.
[21] D. Hajage, Y. De Rycke, G. Chauvet, F. Tubach (2016), Estimation of conditional and marginal odds ratios using the prognostic score. Statistics in Medicine, vol n° 36(4), pp 687-716.
[20] G. Chauvet (2017), A comparison of pivotal sampling and unequal probability sampling with replacement. Statistics and Probability Letters, vol n° 121, pp 1-5. [Supplementary Material]
[19] H. Juillard, G. Chauvet, A. Ruiz-Gazen (2017), Estimation under cross-classified sampling with application to a childhood survey. Journal of the American Statistical Association, vol n°112(518), pp 850-858.
[18] H. Boistard, G. Chauvet, D. Haziza (2016), Doubly robust inference for the distribution function in the presence of missing survey data. Scandinavian Journal of Statistics, vol n°43(3), pp 683-699.
[17] G. Chauvet, D. Haziza et E. Lesage (2016), Examining some aspects of balanced sampling in surveys. Statistica Sinica, vol n°27, pp 313-334.
[16] G. Chauvet (2016), Variance Estimation for the 2006 French Housing Survey. Mathematical Population Studies, vol 23, n°3, pp 147-163. [Présentation]
[15] G. Chauvet (2015), Coupling Methods for multistage sampling. Annals of Statistics, vol 43, n°6, pp 2484-2506.[Présentation]
[14] D. Haziza, C-O. Nambeu, G. Chauvet (2014), Doubly robust imputation procedures for populations containing a large amount of zeroes in surveys. Canadian Journal of Statistics, vol 42, n°4, pp 650-669.
[13] G. Chauvet, G. Tandeau de Marsac (2014), Méthodes d'estimation sur bases de sondage multiples dans le cadre de plans de sondage à deux degrés. Technique d'Enquêtes, vol 40, n°2, pp 367-378. [Présentation]
[12] F.J. Breidt, G. Chauvet (2012), Penalized Balanced Sampling. Biometrika, vol 99, n° 4, pp 945-958.
[11] G. Chauvet (2012), On a characterization of ordered pivotal sampling. Bernoulli, vol 18, n° 4, pp 1320-1340.
[10] G. Chauvet, D. Haziza (2012), Fully efficient estimation of coefficients of correlation in the presence of imputed data. Canadian Journal of Statistics, vol. 40, n° 1, pp 124-149.
[9] M. Chandesris, G. Chauvet, J.C. Deville (2011), Allocation optimale pour un plan à plusieurs degrés. Application à l’estimation de la fraude tarifaire grandes lignes à la SNCF. Journal de la SFdS, vol. 152, n° 4, pp. 47-59.
[8] G. Chauvet (2011), On variance estimation for the French Master Sample. Journal of Official Statistics, vol. 27, n° 4, pp. 651–668. [Présentation]
[7] G. Chauvet, J.C. Deville, D. Haziza (2011), On balanced random imputation in surveys. Biometrika, vol. 98, pp. 459-471. [Présentation]
[6] G. Chauvet, D. Bonnery, J.C. Deville (2011), Optimal inclusion probabilities for balanced sampling. Journal of Statistical Planning and Inference, vol 141, pp. 984 - 994. [Présentation]
[5] F.J. Breidt, G. Chauvet (2011), Improved variance estimation for balanced samples drawn via the Cube method. Journal of Statistical Planning and Inference, vol 141, pp. 479 - 487. [Présentation]
[4] D. Haziza, G. Chauvet, J.C. Deville (2010), A note on sampling and estimation in the presence of cut-off sampling. Australian and New Zealand Journal of Statistics, vol 52, pp. 303 - 319.
[3] G. Chauvet (2009), Stratified Balanced Sampling, Survey Methodology, vol 35, pp. 115 - 119.
[2] G. Chauvet, Y. Tillé (2007), Application of Fast SAS Macros for Balancing Samples to the Selection of Addresses, Case Studies in Business, Industry and Government Statistics, vol 2, pp. 173 - 182.
[1] G. Chauvet, Y. Tillé (2006), A fast algorithm of Balanced Sampling, Computational Statistics, vol 21, pp. 53 - 61.
Articles soumis ou en préparation
[41] G. Chauvet, M. Gerber (202x), Exponential inequalities for sampling designs.
[42] T-H. Vo, V. Garès, L-C. Zhang, A. Happe, E. Oger, S. Paquelet, G. Chauvet (202X), Cox regression with linked data. In revision for Statistics in Medicine.
[43] J. Rubin, G. Chauvet (202X), Bootstrap methods for cross-classified sampling designs.
[44] M-A. Metten, N. Costet, J-F. Viel, G. Chauvet (202X), Reflection on modern methods: a note on variance estimation when using inverse probability weighting to handle attrition in cohort studies.
[45] O. Bouriaud, P. Brion, G. Chauvet (202X), The weight share method in forest inventories: why we need plots to sample trees.
[46] D. Hajage, G. Chauvet, Y. De Rycke, F. Tubach (201X), Variance estimation when weighting using the estimated propensity score to estimate a treatment effect on a binary outcome.
[47] E. Anceaume, Y. Busnel, G. Chauvet, N. Rivetti (201X). Pivotal sampling in datastreams with estimation on sliding windows.
[48] G. Chauvet (201X), Bootstrap for multistage sampling and unequal probability sampling of primary sampling units.[49] G. Chauvet (201X), Simplified variance estimation for multistage sample surveys.
[50] G. Chauvet (201X), A note on the consistency of the Narain-Horvitz-Thompson estimator.