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17 results on '"Bordes, Laurent"'

1. Semiparametric Methods for Virtual Age Models

Author

Beutner, Eric, Bordes, Laurent, Doyen, Laurent, Department of Quantitative Economics [Maastricht], Maastricht University [Maastricht], Laboratoire de Mathématiques et de leurs Applications [Pau] (LMAP), Université de Pau et des Pays de l'Adour (UPPA)-Centre National de la Recherche Scientifique (CNRS), Applied Statistics And Reliability - ASAR (ASAR ), Laboratoire Jean Kuntzmann (LJK ), and Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019])-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019])

Subjects
[MATH.MATH-ST]Mathematics [math]/Statistics [math.ST], ComputingMilieux_MISCELLANEOUS
Abstract

International audience

Published
2019

2. OR03: UN NOUVEL ESTIMATEUR BAYÉSIEN DE TAUX DE DÉFAILLANCE POUR TRAITER L'HÉTÉROGÉNÉITÉ DES DONNÉES EXTRAITES D'OREDA

Author

Mercier, Sophie, Bordes, Laurent, Clavé, Nicolas, Cacheux, Pierre-Joseph, Laboratoire de Mathématiques et de leurs Applications [Pau] (LMAP), Université de Pau et des Pays de l'Adour (UPPA)-Centre National de la Recherche Scientifique (CNRS), Université de Pau et des Pays de l'Adour (UPPA), and TOTAL

Subjects
[STAT]Statistics [stat], [MATH.MATH-PR]Mathematics [math]/Probability [math.PR], [STAT.ML]Statistics [stat]/Machine Learning [stat.ML], [MATH.MATH-ST]Mathematics [math]/Statistics [math.ST], [INFO.INFO-MO]Computer Science [cs]/Modeling and Simulation, ComputingMilieux_MISCELLANEOUS
Abstract

International audience

Published
2018

3. Semi-parametric inference for effective age models when the age function is specified parametrically

Author

Beutner, Eric, Bordes, Laurent, Doyen, Laurent, Department of Quantitative Economics [Maastricht], Maastricht University [Maastricht], Université de Pau et des Pays de l'Adour (UPPA), Fiabilité et Géométrie Aléatoire (FIGAL), Laboratoire Jean Kuntzmann (LJK ), and Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019])-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019])

Subjects
[MATH.MATH-ST]Mathematics [math]/Statistics [math.ST], ComputingMilieux_MISCELLANEOUS
Abstract

International audience

Published
2017

4. Consistent semiparametric estimation with recurrent event data based on virtual age models

Author

Beutner, Eric, Bordes, Laurent, Doyen, Laurent, Department of Quantitative Economics [Maastricht], Maastricht University [Maastricht], Université de Pau et des Pays de l'Adour (UPPA), Fiabilité et Géométrie Aléatoire (FIGAL), Laboratoire Jean Kuntzmann (LJK ), and Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019])-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019])

Subjects
[MATH.MATH-ST]Mathematics [math]/Statistics [math.ST], ComputingMilieux_MISCELLANEOUS
Abstract

International audience

Published
2017

5. The failure of the profile likelihood method for semi-parametric effective age models

Author

Beutner, Eric, Bordes, Laurent, Doyen, Laurent, Department of Quantitative Economics [Maastricht], Maastricht University [Maastricht], Laboratoire de Mathématiques et de leurs Applications [Pau] (LMAP), Université de Pau et des Pays de l'Adour (UPPA)-Centre National de la Recherche Scientifique (CNRS), Fiabilité et Géométrie Aléatoire (FIGAL), Laboratoire Jean Kuntzmann (LJK ), Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019])-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019]), and ANR-11-BS01-0021,AMMSI,Vieillissement et maintenance en fiabilité : modélisation et inférence statistique(2011)

Subjects
Effective age process, Recurrent event data, [MATH.MATH-ST]Mathematics [math]/Statistics [math.ST], Cox’s proportional hazards model, Semi-parametric statistical model, Accelerated failure time model, Profile likelihood inference, virtual age process
Abstract

International audience; We consider a semi-parametric model for recurrent events. The model consists of an unknown hazard rate function, the infinite-dimensional parameter of the model, and a parametrically specified effective age function. We will present a condition on the family of effective age functions under which the profile likelihood function evaluated at the parameter vector θ, say, exceeds the profile likelihood function evaluated at the parameter vector $\tilde\theta$, say, with probability p. From this we derive a condition under which profile likelihood inference for the finite-dimensional parameter of the model leads to inconsistent estimates. Examples will be presented. In particular, we will provide an example where the profile likelihood function is monotone with probability one regardless of the true data generating process.

Published
2017
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6. Semiparametric consistent estimators for virtual age models under right censoring

Author

Beutner, Eric, Bordes, Laurent, Doyen, Laurent, Department of Quantitative Economics [Maastricht], Maastricht University [Maastricht], Université de Pau et des Pays de l'Adour (UPPA), Fiabilité et Géométrie Aléatoire (FIGAL), Laboratoire Jean Kuntzmann (LJK ), and Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019])-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019])

Subjects
[MATH.MATH-ST]Mathematics [math]/Statistics [math.ST], ComputingMilieux_MISCELLANEOUS
Abstract

International audience

Published
2016

7. Stochastic EM-like Algorithms for Fitting Finite Mixture of Lifetime Regression Models Under Right Censoring

Author

Bordes, Laurent, Chauveau, Didier, Laboratoire de Mathématiques et de leurs Applications [Pau] (LMAP), Université de Pau et des Pays de l'Adour (UPPA)-Centre National de la Recherche Scientifique (CNRS), Mathématiques - Analyse, Probabilités, Modélisation - Orléans (MAPMO), Centre National de la Recherche Scientifique (CNRS)-Université d'Orléans (UO), American Statistical Association, and Alexandria, VA: American Statistical Association

Subjects
Right censoring, [MATH.MATH-ST]Mathematics [math]/Statistics [math.ST], proportional hazards model, Statistics::Methodology, EM algorithm, semiparametric mixture models
Abstract

International audience; Finite mixture of models based on the proportional hazards or the accelerated failure time assumption lead to a large variety of lifetime regression models. We present several iterative methods based on EM and Stochastic EM methodologies, that allow fitting parametric or semiparametric mixture of lifetime regression models for randomly right censored lifetime data including covariates. Their identifiability is briefly discussed and in the semiparametric case we show that simulating the missing data coming from the mixture allows to use the ordinary partial likelihood inference method in an EM algorithm's M-step. The effectiveness of the new proposed algorithms is illustrated through simulation studies.

Published
2016

8. A large class of models for recurrent events for which profile likelihood inference fails

Author

Beutner, Eric, Bordes, Laurent, Doyen, Laurent, Department of Quantitative Economics [Maastricht], Maastricht University [Maastricht], Université de Pau et des Pays de l'Adour (UPPA), Fiabilité et Géométrie Aléatoire (FIGAL), Laboratoire Jean Kuntzmann (LJK), and Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Centre National de la Recherche Scientifique (CNRS)-Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Centre National de la Recherche Scientifique (CNRS)

Subjects
[MATH.MATH-ST]Mathematics [math]/Statistics [math.ST], ComputingMilieux_MISCELLANEOUS
Abstract

International audience

Published
2015

9. Virtual age model with unknown event effects

Author

Beutner, Eric, Bordes, Laurent, Doyen, Laurent, Department of Quantitative Economics [Maastricht], Maastricht University [Maastricht], Laboratoire de Mathématiques et de leurs Applications [Pau] (LMAP), Université de Pau et des Pays de l'Adour (UPPA)-Centre National de la Recherche Scientifique (CNRS), Fiabilité et Géométrie Aléatoire (FIGAL), Laboratoire Jean Kuntzmann (LJK), Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Centre National de la Recherche Scientifique (CNRS)-Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Centre National de la Recherche Scientifique (CNRS), and ANR-11-BS01-0021,AMMSI,Vieillissement et maintenance en fiabilité : modélisation et inférence statistique(2011)

Subjects
[MATH.MATH-ST]Mathematics [math]/Statistics [math.ST], ComputingMilieux_MISCELLANEOUS
Abstract

International audience

Published
2015

10. On a large class of models for recurrent events for which profile likelihood inference fails

Author

Beutner, Eric, Bordes, Laurent, Doyen, Laurent, Department of Quantitative Economics [Maastricht], Maastricht University [Maastricht], Laboratoire de Mathématiques et de leurs Applications [Pau] (LMAP), Université de Pau et des Pays de l'Adour (UPPA)-Centre National de la Recherche Scientifique (CNRS), Fiabilité et Géométrie Aléatoire (FIGAL), Laboratoire Jean Kuntzmann (LJK), Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Centre National de la Recherche Scientifique (CNRS)-Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Centre National de la Recherche Scientifique (CNRS), and ANR-11-BS01-0021,AMMSI,Vieillissement et maintenance en fiabilité : modélisation et inférence statistique(2011)

Subjects
[MATH.MATH-ST]Mathematics [math]/Statistics [math.ST], ComputingMilieux_MISCELLANEOUS
Abstract

International audience

Published
2015

11. Failure of the profile likelihood method for semi-parametric virtual age models

Author

Beutner, Eric, Bordes, Laurent, Doyen, Laurent, Department of Quantitative Economics [Maastricht], Maastricht University [Maastricht], Laboratoire de Mathématiques et de leurs Applications [Pau] (LMAP), Université de Pau et des Pays de l'Adour (UPPA)-Centre National de la Recherche Scientifique (CNRS), Fiabilité et Géométrie Aléatoire (FIGAL), Laboratoire Jean Kuntzmann (LJK), Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Centre National de la Recherche Scientifique (CNRS)-Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Centre National de la Recherche Scientifique (CNRS), and ANR-11-BS01-0021,AMMSI,Vieillissement et maintenance en fiabilité : modélisation et inférence statistique(2011)

Subjects
[MATH.MATH-ST]Mathematics [math]/Statistics [math.ST], ComputingMilieux_MISCELLANEOUS
Abstract

International audience

Published
2015

12. Semiparametric estimation of a mixture of two linear regressions in which one component is known

Author

Bordes, Laurent, Kojadinovic, Ivan, Vandekerkhove, Pierre, Laboratoire de Mathématiques et de leurs Applications [Pau] (LMAP), Université de Pau et des Pays de l'Adour (UPPA)-Centre National de la Recherche Scientifique (CNRS), Probabilité et Statistique, Laboratoire d'Analyse et de Mathématiques Appliquées (LAMA), Centre National de la Recherche Scientifique (CNRS)-Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12)-Fédération de Recherche Bézout-Université Paris-Est Marne-la-Vallée (UPEM)-Centre National de la Recherche Scientifique (CNRS)-Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12)-Fédération de Recherche Bézout-Université Paris-Est Marne-la-Vallée (UPEM), Université Paris-Est Marne-la-Vallée (UPEM)-Fédération de Recherche Bézout-Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12)-Centre National de la Recherche Scientifique (CNRS)-Université Paris-Est Marne-la-Vallée (UPEM)-Fédération de Recherche Bézout-Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12)-Centre National de la Recherche Scientifique (CNRS), and Kojadinovic, Ivan

Subjects
[STAT.TH] Statistics [stat]/Statistics Theory [stat.TH], [MATH.MATH-ST]Mathematics [math]/Statistics [math.ST], [STAT.TH]Statistics [stat]/Statistics Theory [stat.TH], [MATH.MATH-ST] Mathematics [math]/Statistics [math.ST]
Abstract

A new estimation method for the two-component mixture model introduced in \cite{Van12} is proposed. This model, which consists of a two-component mixture of linear regressions in which one component is entirely known while the proportion, the slope, the intercept and the error distribution of the other component are unknown, seems to be of interest for the analysis of large datasets produced from two-color ChIP-chip high-density microarrays. In spite of good performance for datasets of reasonable size, the method proposed in \cite{Van12} suffers from a serious drawback when the sample size becomes large, as it is based on the optimization of a contrast function whose pointwise computation requires $O(n^2)$ operations. The range of applicability of the method derived in this work is substantially larger as it is based on a method-of-moment estimator whose computation only requires $O(n)$ operations. From a theoretical perspective, the asymptotic normality of both the estimator of the Euclidean parameter vector and of the semiparametric estimator of the c.d.f.\ of the error is proved under weak conditions not involving the zero-symmetry assumption typically used this last decade. The finite-sample performance of the latter estimators is studied under various scenarios through Monte Carlo experiments. From a more practical perspective, the proposed method is applied to the tone data analyzed, among others, by \cite{HunYou12}, and to the ChIPmix data studied by \cite{MarMarBer08}. An extension of the considered model involving an unknown scale parameter for the first component is discussed in the final section.

Published
2013

13. EM and Stochastic EM algorithms for reliability mixture models under random censoring

Author

Bordes, Laurent, Chauveau, Didier, Laboratoire de Mathématiques et de leurs Applications [Pau] (LMAP), Université de Pau et des Pays de l'Adour (UPPA)-Centre National de la Recherche Scientifique (CNRS), Mathématiques - Analyse, Probabilités, Modélisation - Orléans (MAPMO), and Centre National de la Recherche Scientifique (CNRS)-Université d'Orléans (UO)

Subjects
Statistics::Theory, survival data, reliability, [MATH.MATH-ST]Mathematics [math]/Statistics [math.ST], finite mixture, [STAT.TH]Statistics [stat]/Statistics Theory [stat.TH], EM algorithm, semiparametric mixtures
Abstract

Mixture models in reliability bring a useful compromise between parametric and nonparametric models, when several failure modes are suspected. The classical methods for estimation in mixture models rarely handle the additional difficulty coming from the fact that lifetime data are often censored, in a deterministic or random way. We present in this paper several iterative methods based on EM and Stochastic EM methodology, that allow us to estimate parametric or semiparametric mixture models for randomly right censored lifetime data, provided they are identifiable. We consider different levels of completion for the (incomplete) observed data, and provide genuine or EM-like algorithms for several situations. In particular, we show that in censored semiparametric situations, a stochastic step is the only practical solution allowing computation of nonparametric estimates of the unknown survival function. The effectiveness of the new proposed algorithms are demonstrated in simulation studies and an actual dataset example.

Published
2012

14. Estimators based on omega-dependent generalized weighted Cramér-von Mises distances under censoring - with applications to mixture models

Author

Beutner, Eric, Bordes, Laurent, Laboratoire de Mathématiques et de leurs Applications [Pau] (LMAP), Université de Pau et des Pays de l'Adour (UPPA)-Centre National de la Recherche Scientifique (CNRS), Amsterdam School of Economics (ASE), and University of Amsterdam [Amsterdam] (UvA)

Subjects
[MATH.MATH-PR]Mathematics [math]/Probability [math.PR], surgical procedures, operative, [MATH.MATH-ST]Mathematics [math]/Statistics [math.ST], TheoryofComputation_LOGICSANDMEANINGSOFPROGRAMS, education, musculoskeletal system, ComputingMethodologies_ARTIFICIALINTELLIGENCE, human activities, ComputingMilieux_MISCELLANEOUS, health care economics and organizations
Abstract

Estimators based on $\omega$-dependent generalized weighted Cramér-vonMises distances are defined for data that are subject to a possible right censorship. The distance between the data, summarized by the Kaplan-Meier estimator, and the target model is allowed to depend on the sample size and, for example, on the number of censored items. It is shown that the estimators are consistent and asymptotically multivariate normal for every $p$ dimensional parametric family fulfilling some mild regularity conditions. The results are applied to finite mixtures. Simulation results for finite mixtures indicate that the estimators are useful for moderate sample sizes. Furthermore, the simulation results reveal the usefulness of sample size dependent and censoring sensitive distance functions for moderate sample sizes. Moreover, the estimators for the mixing proportion seems to be fairly robust against a 'symmetric' contamination model even when ensoring is present.

Published
2011

15. Combining Gamma and Brownian processes for degradation modeling in presence of explanatory variables

Author

Bordes, Laurent, Paroissin, Christian, Salami, Ali, Laboratoire de Mathématiques et de leurs Applications [Pau] (LMAP), and Université de Pau et des Pays de l'Adour (UPPA)-Centre National de la Recherche Scientifique (CNRS)

Subjects
Wiener process, [MATH.MATH-ST]Mathematics [math]/Statistics [math.ST], Gamma process, 62F10, 62F12, 62N05, Asymptotic normality, Consistency, [STAT.TH]Statistics [stat]/Statistics Theory [stat.TH], Covariates, [STAT.ME]Statistics [stat]/Methodology [stat.ME], Least-square estimators
Abstract

A new approach has been proposed recently to describe a system deterioration. In this new approach the authors have considered the degradation as the sum of a gamma process and a Brownian motion, independent of the gamma process. The Brownian motion may describe, for example, degradation measurement error. In this paper covariates are introduced in order to take into account environmental effects or systems heterogeneity. From the observation of $n$ independent items at regular instants over a finite time interval, the model parameters are estimated by a two-stage least-square method. Asymptotic properties of the estimators are provided. Finally both numerical simulations and real data applications are supplied to illustrate our method.

Published
2010

16. Early detection of change-point in hazard rate with small sample size

Author

Bordes, Laurent, Ibled, Frédéric, Paroissin, Christian, Turlot, Jean-Christophe, Laboratoire de Mathématiques et de leurs Applications [Pau] (LMAP), Université de Pau et des Pays de l'Adour (UPPA)-Centre National de la Recherche Scientifique (CNRS), and Alstom Transport (Alstom Transport)

Subjects
Mann-Whitney test, Statistical tables, [STAT.AP]Statistics [stat]/Applications [stat.AP], [MATH.MATH-ST]Mathematics [math]/Statistics [math.ST], Change-point, Exponential distribution, [STAT.TH]Statistics [stat]/Statistics Theory [stat.TH], Hazard rate, 62N05, 62Q05, 62P30, [STAT.ME]Statistics [stat]/Methodology [stat.ME], Precedence test
Abstract

In this paper we address the problem of deciding if either $n$ consecutive independent failure times have the same failure rate or if there exists some $k\in\{1,\ldots,n\}$ such that the common failure rate of the first $k$ failure times is different from the common failure rate of the last $n-k$ failure times. The statistical tests we propose are based on mean ratio under the assumption that lifetimes are exponentially distributed and on Mann-Whitney or precedence test statistics when no parametric assumption on the underlying distribution is done. Our statistics are free of the unknown underlying distribution under the null hypothesis of homogeneity of the $n$ failure times which allows to compute critical values of our tests by Monte Carlo methods for small sample size. These tests have been developed in order to perform sequential change-point analysis of small sets of feedback data. They are applied to feedback data from Alstom Transport in order to detect an early change-point of the failure rate of an industrial equipment.

Published
2010

17. Semi- and non-parametric competing risks analysis of right censored data and failure cause missing completely at random

Author

Bordes, Laurent, Dauxois, Jean-Yves, Joly, Pierre, Laboratoire de Mathématiques et de leurs Applications [Pau] (LMAP), Université de Pau et des Pays de l'Adour (UPPA)-Centre National de la Recherche Scientifique (CNRS), Laboratoire de Mathématiques de Besançon (UMR 6623) (LMB), Université de Bourgogne (UB)-Université de Franche-Comté (UFC), Université Bourgogne Franche-Comté [COMUE] (UBFC)-Université Bourgogne Franche-Comté [COMUE] (UBFC)-Centre National de la Recherche Scientifique (CNRS), Institut de Santé Publique, d'Epidémiologie et de Développement (ISPED), and Université Bordeaux Segalen - Bordeaux 2

Subjects
survival analysis, Statistics::Theory, Additive hazards, reliability, Statistics::Applications, [MATH.MATH-ST]Mathematics [math]/Statistics [math.ST], Statistics::Methodology, 62G20, 62N01, 62N05, counting processes, competing risks, missing failure cause
Abstract

We consider a nonparametric and a semiparametric (in presence of covariates) additive hazards rate competing risks model with censoring and failure cause possibly missing completely at random. Estimators of the unknown parameters are proposed in order to satisfy some optimality criteria. Large ample results are given for all the estimators. Our nonparametric method is applied to a real data set and the behavior of the semiparametric estimators are analyzed through a Monte Carlo study.

Published
2007

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