Laboratoire de Mathématiques de Besançon - UMR 6623 CNRS

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30 novembre 2020: 1 événement

  • Planning des séminaires 2020-2021

    Lundi 30 novembre 11:00-12:00 - Mehdi Dagdoug - LmB, Univ. Bourgogne Franche-Comté

    Séminaire PS : Model-assisted estimation through random forests in finite population sampling

    Résumé : Estimation of finite population totals is of primary interest in survey sampling. Often, additional auxiliary information is available at the population level. The model-assisted approach uses this supplementary source of information to construct improved estimators of finite population totals by assuming a model between the survey variable and the potential predictors. In this work, new classes of model-assisted estimators based on random forests are suggested.
    Under mild conditions, the proposed estimators are shown to be asymptotically design unbiased and consistent. Their asymptotic variance is derived, and a consistent variance estimator is suggested. The asymptotic distribution of the estimators is obtained, allowing for the use of normal-based confidence intervals. The high-dimensional behavior of the random forest estimator is also investigated and compared to commonly used estimators. Simulations illustrate that the proposed model is particularly efficient and can outperform state-of-the-art estimators, especially in complex settings such as small sample sizes, high-dimensional regressor space or complex superpopulation models. This is a joint work with Camelia Goga and David Haziza.

    En savoir plus : Planning des séminaires 2020-2021