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Your search keyword '"Comte , Fabienne"' showing total 10 results
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10 results on '"Comte , Fabienne"'

1. Quadratic functional estimation from observations with multiplicative measurement error

Author

Neubert, Bianca, Comte, Fabienne, and Johannes, Jan

Subjects
Mathematics - Statistics Theory, Primary 62G05, Secondary 62G07
Abstract

We consider the nonparametric estimation of the value of a quadratic functional evaluated at the density of a strictly positive random variable $X$ based on an iid. sample from an observation $Y$ of $X$ corrupted by an independent multiplicative error $U$. Quadratic functionals of the density covered are the $\mathbb{L}^2$-norm of the density and its derivatives or the survival function. We construct a fully data-driven estimator when the error density is known. The plug-in estimator is based on a density estimation combining the estimation of the Mellin transform of the $Y$ density and a spectral cut-off regularized inversion of the Mellin transform of the error density. The main issue is the data-driven choice of the cut-off parameter using a Goldenshluger-Lepski-method. We discuss conditions under which the fully data-driven estimator attains oracle-rates up to logarithmic deteriorations. We compute convergence rates under classical smoothness assumptions and illustrate them by a simulation study., Comment: 42 page

Published
2024

2. Nonparametric Estimation of the Transition Density Function for Diffusion Processes

Author

Comte, Fabienne and Marie, Nicolas

Subjects
Mathematics - Statistics Theory
Abstract

We assume that we observe $N$ independent copies of a diffusion process on a time-interval $[0,2T]$. For a given time $t$, we estimate the transition density $p_t(x,y)$, namely the conditional density of $X_{t + s}$ given $X_s = x$, under conditions on the diffusion coefficients ensuring that this quantity exists. We use a least squares projection method on a product of finite dimensional spaces, prove risk bounds for the estimator and propose an anisotropic model selection method, relying on several reference norms. A simulation study illustrates the theoretical part for Ornstein-Uhlenbeck or square-root (Cox-Ingersoll-Ross) processes., Comment: 32 pages, 5 figures

Published
2024

3. Nonparametric Drift Estimation from Diffusions with Correlated Brownian Motions

Author

Comte, Fabienne and Marie, Nicolas

Subjects
Mathematics - Statistics Theory
Abstract

In the present paper, we consider that $N$ diffusion processes $X^1,\dots,X^N$ are observed on $[0,T]$, where $T$ is fixed and $N$ grows to infinity. Contrary to most of the recent works, we no longer assume that the processes are independent. The dependency is modeled through correlations between the Brownian motions driving the diffusion processes. A nonparametric estimator of the drift function, which does not use the knowledge of the correlation matrix, is proposed and studied. Its integrated mean squared risk is bounded and an adaptive procedure is proposed. Few theoretical tools to handle this kind of dependency are available, and this makes our results new. Numerical experiments show that the procedure works in practice., Comment: 28 pages, 4 figures

Published
2022
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8. Intermediate-dose versus low-dose low-molecular-weight heparin in pregnant and post-partum women with a history of venous thromboembolism (Highlow study): an open-label, multicentre, randomised, controlled trial

Author

Bistervels, Ingrid M, primary, Buchmüller, Andrea, additional, Wiegers, Hanke M G, additional, Ní Áinle, Fionnuala, additional, Tardy, Bernard, additional, Donnelly, Jennifer, additional, Verhamme, Peter, additional, Jacobsen, Anne F, additional, Hansen, Anette T, additional, Rodger, Marc A, additional, DeSancho, Maria T, additional, Shmakov, Roman G, additional, van Es, Nick, additional, Prins, Martin H, additional, Chauleur, Céline, additional, Middeldorp, Saskia, additional, van den Akker, Eline S, additional, Bekker, Mireille N, additional, van Bemmel, Thomas, additional, Bertoletti, Laurent, additional, Blanc, Julie, additional, Bleker, Suzanne M, additional, Bourtembourg-Matras, Aude, additional, Bretelle, Florence, additional, Byrne, Bridgette, additional, Couturaud, Francis, additional, Delorme, Pierre, additional, Eerenberg, Elise S, additional, Franssen, Maureen TM, additional, Fuglsang, Jens, additional, Ganzevoort, Wessel, additional, Goffinet, François, additional, de Haan-Jebbink, Jiska M, additional, Heidema, Wieteke, additional, Hertzberg, Monique A, additional, Hovens, Marcel MC, additional, Huisman, Menno V, additional, de Jong-Speksnijder, Leonie, additional, Kamphuisen, Pieter-Willem, additional, O'Keeffe, Denis J, additional, Lacut, Karine, additional, Langenveld, Josje, additional, Lunshof, M Simone, additional, Martens, Caroline P, additional, Merah, Adel, additional, Le Moigne, Emmanuelle, additional, Papatsonis, Dimitri NM, additional, Pernod, Gilles, additional, Perrotin, Franck, additional, Peynaud-Debayle, Edith, additional, Pierre, Fabrice, additional, Plu Bureau, Geneviève, additional, Raia-Barjat, Tiphaine, additional, Rijnders, Robbert JP, additional, Rosario, Roger, additional, Ruivard, Marc, additional, Schmidt, Jeannot, additional, Sueters, Marieke, additional, Vanassche, Thomas, additional, Varlet, Marie-Noëlle, additional, Vivanti, Alexandre J, additional, van der Vlist, Matthieu Y, additional, van der Voet, Lucet F, additional, Vollebregt, Karlijn C, additional, de Vries, Johanna IP, additional, de Weerd, Sabina, additional, Westerweel, Peter E, additional, Wijnberger, Lia DE, additional, ten Wolde, Marije, additional, Ypma, Paula F, additional, Zuily-Lamy, Catherine, additional, Zwart, Joost J, additional, Benachi, Alexandra, additional, Beucher, Gaël, additional, Bezanahary, Holy, additional, de Boer, Karin, additional, de Boer, Marjon A., additional, Bousquet, Frantz, additional, Bremer, Henk A., additional, Bressollette, Luc, additional, Brossard, Aurélie, additional, Chau, Cécile, additional, Cleary, Brian, additional, Comte, Fabienne, additional, Corsini, Thomas, additional, Coustel, Anne, additional, Debaveye, Barbara, additional, Desbrière, Raoul, additional, Duvillard, Cécile, additional, Eckman, Astrid, additional, Eikenboom, Jeroen, additional, Elias, Antoine, additional, Faber, Laura M., additional, Ferrari, Emile, additional, Gallot, Denis, additional, Gauchotte, Emilie, additional, Gaugler, Ingrid, additional, Geerlings, Abby E., additional, O'Gorman, Audrey, additional, Grobost, Vincent, additional, de Groot, Pieter-Kees, additional, van der Ham, David P., additional, Hermsen, Brenda, additional, Kamphorst, Kim, additional, Karovitch, Alan, additional, Kleiverda, Gunilla, additional, Kloster, Aiste, additional, Koops, Annemarieke, additional, Krabbendam, Inneke, additional, Kruip, Marieke J.H.A., additional, Kuipers, Saskia, additional, van Laar, Judith, additional, Laneelle, Damien, additional, Lima, Suzanne, additional, MacMahon, Peter, additional, Mandelbrot, Laurent, additional, van Meir, Claudia A., additional, Menez, Caroline, additional, Morssink, Leonard P., additional, Moulin, Nathalie, additional, Mousty, Eve, additional, Muller, Matthieu, additional, Murphy, Lucy, additional, Peerlinck, Kathelijne, additional, O'Reilly, Alma, additional, de Reus, Maartje, additional, Le Roux, Magali Hilmi, additional, Ryan, Kevin, additional, Samren, Bettina, additional, Schippers, Daniela, additional, Schuitemaker, Nico, additional, Schweizer, Chloé, additional, van der Straaten, Hanneke, additional, Tromeur, Cécile, additional, Vanheule, Kristine, additional, Verhagen, Tamara, additional, Visser, Jantien, additional, Watts, Michael, additional, van Wijngaarden, Wim J., additional, Woiski, Mallory, additional, and Zelis, Maartje, additional

Published
2022
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9. Should we estimate a product of density functions by a product of estimators ?

Author

Comte, Fabienne, Duval, Céline, Mathématiques Appliquées Paris 5 (MAP5 - UMR 8145), Université Paris Descartes - Paris 5 (UPD5)-Institut National des Sciences Mathématiques et de leurs Interactions (INSMI)-Centre National de la Recherche Scientifique (CNRS), Laboratoire Paul Painlevé - UMR 8524 (LPP), Centre National de la Recherche Scientifique (CNRS)-Université de Lille, Laboratoire Paul Painlevé (LPP), and Université de Lille-Centre National de la Recherche Scientifique (CNRS)

Subjects
Statistics and Probability, Projection estimator AMS Classification, Density estimation, Kernel estimation, Penalized Comparison to Overfitting, [MATH.MATH-ST]Mathematics [math]/Statistics [math.ST], 62G05-62G07, Bandwidth selection, Statistics, Probability and Uncertainty, Model selection, Nonparametric estimation
Abstract

International audience; In this paper, we consider the inverse problem of estimating the product f g of two densities, given a n-sample of i.i.d. observations drawn from each. We propose both projection estimators with model selection device and kernel estimators with bandwidth selection strategies. The procedures do not consist in making the product of each density estimator, but in plugging an overfitted estimator of one of the two densities, in an estimator based on the second sample. Our findings are a first step toward a better understanding of the good performances of overfitting in regression Nadaraya-Watson estimator.

Published
2022
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10. Hazard regression with noncompactly supported bases.

Author

Brunel, Elodie and Comte, Fabienne

Subjects
*GAMMA functions, *HAZARD function (Statistics), *HAZARDS, *NONPARAMETRIC estimation, *LEAST squares
Abstract

In this article, we consider the problem of nonparametric hazard rate estimation in the presence of right‐censored observations. We provide a generalized risk bound for a regression‐type nonparametric estimator of the hazard function of interest. Under adequate integrability conditions, our bound is a generalization of estimation strategies specific to compactly supported bases to bases that are not necessarily compactly supported. We show that it encompasses previous compact‐support results and interestingly represents hazard rates as combinations of gamma functions. We discuss the model selection method, which comes out from the new terms of the risk bounds, and compare the performance of the new estimator to that of previous ones, when using a noncompact Laguerre basis. A real data example is also presented. [ABSTRACT FROM AUTHOR]

Published
2021
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