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Your search keyword '"Bar-Hen, Avner"' showing total 3 results
Start Over Author "Bar-Hen, Avner" Topic estimation theory
3 results on '"Bar-Hen, Avner"'

1. Influence measures and stability for graphical models.

Author

Bar-Hen, Avner and Poggi, Jean-Michel

Subjects
*GENE expression, *JACKKNIFE (Statistics), *ALGORITHMS, *ESTIMATION theory, *STABILITY theory, *MATHEMATICAL models
Abstract

Graphical models allow to represent a set of random variables together with their probabilistic conditional dependencies. Various algorithms have been proposed to estimate such models from data. The focus of this paper is on individual observations diagnosis issues. The use of an influence measure is a classical diagnostic method to measure the perturbation induced by a single element, in other terms we consider stability issue through jackknife. For a given graphical model, we provide tools to perform diagnosis on observations. In a second step we propose a filtering of the dataset to obtain a stable network. All along the paper an application to a gene expression dataset illustrates the proposals. [ABSTRACT FROM AUTHOR]

Published
2016
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2. A semi-parametric approach for mixture models: Application to local false discovery rate estimation

Author

Robin, Stéphane, Bar-Hen, Avner, Daudin, Jean-Jacques, and Pierre, Laurent

Subjects
*ESTIMATION theory, *MATHEMATICAL statistics, *DATA analysis, *FUNCTIONAL analysis
Abstract

Abstract: A procedure to estimate a two-component mixture model where one component is known is proposed. The unknown part is estimated with a weighted kernel function. The weights are defined in an adaptive way. The convergence to a unique solution of our estimation procedure is proven. The procedure is compared with two classical approaches using simulation. In addition, the results obtained are applied to multiple testing procedure in order to estimate the posterior population probabilities and the local false discovery rate. [Copyright &y& Elsevier]

Published
2007
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3. Asymptotic distribution of density-dependent stage-grouped population dynamics models

Author

Mélanie Zetlaoui, Nicolas Picard, Avner Bar-Hen, Organisation et Modélisation de l'Information et des Processus (OMIP-INAPG), Institut National de la Recherche Agronomique (INRA), Dynamique des forêts naturelles (Cirad-Es-UPR 37 Dynamique forestière), Département Environnements et Sociétés (Cirad-ES), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad), Mathématiques Appliquées Paris 5 (MAP5 - UMR 8145), Centre National de la Recherche Scientifique (CNRS)-Institut National des Sciences Mathématiques et de leurs Interactions (INSMI)-Université Paris Descartes - Paris 5 (UPD5), Bar-Hen, Avner, Université Paris Descartes - Paris 5 (UPD5)-Institut National des Sciences Mathématiques et de leurs Interactions (INSMI)-Centre National de la Recherche Scientifique (CNRS), Organisation et Modélisation de l'Information et des Processus ( OMIP-INAPG ), Institut National de la Recherche Agronomique ( INRA ), Dynamique des forêts naturelles ( Dynamique forestière ), Centre de Coopération Internationale en Recherche Agronomique pour le Développement ( CIRAD ), Mathématiques Appliquées à Paris 5 ( MAP5 - UMR 8145 ), Université Paris Descartes - Paris 5 ( UPD5 ) -Institut National des Sciences Mathématiques et de leurs Interactions-Centre National de la Recherche Scientifique ( CNRS ), Dynamique des forêts naturelles (UPR Dynamique forestière), and Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)

Subjects
0106 biological sciences, Population Dynamics, forêt tropicale, sampling variability, Parameter space, 01 natural sciences, Matrix (mathematics), [MATH.MATH-ST]Mathematics [math]/Statistics [math.ST], Statistics, Dynamique des populations, [MATH.MATH-ST] Mathematics [math]/Statistics [math.ST], General Environmental Science, Mathematics, [SDV.EE]Life Sciences [q-bio]/Ecology, environment, 0303 health sciences, education.field_of_study, U10 - Informatique, mathématiques et statistiques, Estimation theory, [STAT.TH] Statistics [stat]/Statistics Theory [stat.TH], Applied Mathematics, Sampling (statistics), General Medicine, [ STAT.TH ] Statistics [stat]/Statistics Theory [stat.TH], [SDV.EE] Life Sciences [q-bio]/Ecology, environment, General Agricultural and Biological Sciences, Modèle mathématique, Population, Asymptotic distribution, Sample (statistics), 010603 evolutionary biology, Models, Biological, General Biochemistry, Genetics and Molecular Biology, [ SDV.EE ] Life Sciences [q-bio]/Ecology, environment, 03 medical and health sciences, Densitométrie, Applied mathematics, [ MATH.MATH-ST ] Mathematics [math]/Statistics [math.ST], asymptotic distribution, Arbre forestier, education, 030304 developmental biology, Equilibrium point, matrix model, Modèle de simulation, [STAT.TH]Statistics [stat]/Statistics Theory [stat.TH], Usher model, density-dependence, K10 - Production forestière, Philosophy, peuplement forestier
Abstract

International audience; Matrix models are widely used in biology to predict the temporal evolution of stage-structured populations. One issue related to matrix models that is often disregarded is the sampling variability. As the sample used to estimate the vital rates of the models are of finite size, a sampling error is attached to parameter estimation, which has in turn repercussions on all the predictions of the model. In this study, we address the question of building confidence bounds around the predictions of matrix models due to sampling variability. We focus on a density-dependent Usher model, the maximum likelihood estimator of parameters, and the predicted stationary stage vector. The asymptotic distribution of the stationary stage vector is specified, assuming that the parameters of the model remain in a set of the parameter space where the model admits one unique equilibrium point. Tests for density-dependence are also incidentally provided. The model is applied to a tropical rain forest in French Guiana.

Published
2008

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