WorldCat Identities

Dauxois, Jean-Yves (19..-....).

Overview
Works: 9 works in 12 publications in 2 languages and 16 library holdings
Roles: Author, Other, Opponent, Thesis advisor
Publication Timeline
.
Most widely held works by Jean-Yves Dauxois
Quelques résultats de fiabilité en données censurées by Jean-Yves Dauxois( Book )

3 editions published in 1996 in French and held by 5 WorldCat member libraries worldwide

Réalisé dans le cadre d'une convention CIFRE avec la société Turbomeca, ce travail porte sur l'analyse de fiabilité des matériels à partir de retour d'expériences. La première partie du travail s'intéresse à des problèmes d'estimation de l'écart à l'exponentialité en données de survie censurées et, pour ce faire, on considère un indicateur de non-constance du temps résiduel moyen. On introduit alors deux statistiques de test pour un test de l'exponentialité contre l'Idmrl (increasing, then decreasing mean residual life) dont on détermine les lois asymptotiques sous l'hypothèse nulle. La deuxième partie du travail s'intéresse à l'utilisation dans les calculs de fiabilité de données de survie sous réparation minimale avec censures non identiquement distribuées. Sous ce modèle, on effectue des estimations non paramétriques de la fonction de répartition et du taux de panne cumulé. Par des techniques de processus de comptage et de martingales, on mène ensuite une étude asymptotique de ces estimateurs. Dans la troisième partie on s'attache à étudier les propriétés asymptotiques des estimateurs bayesiens non paramétriques introduits par Hjort. Pour cela, on utilise des techniques similaires à celles de la partie précedente. La dernière partie du travail porte sur la présentation par simulation (les données réelles étant confidentielles) des applications numériques réalisées pour Turbomeca
Développement d'une approche basée sur les modèles dynamiques compartimentaux pour évaluer le bénéfice et l'impact des nouveaux médicaments en population générale : application au cas de l'hépatite C by Arnaud Nucit( Book )

2 editions published in 2016 in English and held by 2 WorldCat member libraries worldwide

Ce travail de thèse s'articule autour de trois parties distinctes abordant chacune un thème précis lié à l'épidémiologie. La première partie de ces travaux s'inscrit dans le cadre de la propagation de virus via l'utilisation de modèles épidémiques. Dans cette partie, sont analysées différentes méthodes d'estimations paramétriques et y sont étudiés la qualité de ces estimateurs. Une application à des virus informatiques est proposée. La deuxième partie de cette thèse propose une méthode d'estimation de la prévalence actuelle du virus de l'hépatite C en France par l'intermédiaire d'un modèle de rétro-calcul associé à un modèle de Markov modélisant l'histoire naturelle de la maladie. Cette méthode et les résultats qui en découlent sont comparés avec les résultats obtenus via l'approche de référence en France. Enfin, la dernière partie s'intéresse à l'étude de l'impact des nouvelles thérapeutiques anti-hépatite C susceptible d'éradiquer le virus à moyen terme. En assimilant la population d'intérêt à un groupement de graphes aléatoires, la propagation du virus est modélisée à partir d'un modèle de métapopulation construit sur la base de données migratoires où les dynamiques de chaque sous-population sont régies par un ensemble d'équations différentielles déterministes. Ce travail doctoral a été réalisé dans le cadre d'une convention CIFRE avec les laboratoires Bristol-Myers Squibb
Analyse statistique de processus stochastiques : application sur des données d'orages by Van-Cuong Do( )

1 edition published in 2019 in English and held by 2 WorldCat member libraries worldwide

The work presented in this PhD dissertation concerns the statistical analysis of some particular cases of the Cox process. In a first part, we study the power-law process (PLP). Since the literature for the PLP is abundant, we suggest a state-of-art for the process. We consider the classical approach and recall some important properties of the maximum likelihood estimators. Then we investigate a Bayesian approach with noninformative priors and conjugate priors considering different parametrizations and scenarios of prior guesses. That leads us to define a family of distributions that we name H-B distribution as the natural conjugate priors for the PLP. Bayesian analysis with the conjugate priors are conducted via a simulation study and an application on real data. In a second part, we study the exponential-law process (ELP). We review the maximum likelihood techniques. For Bayesian analysis of the ELP, we define conjugate priors: the modified- Gumbel distribution and Gamma-modified-Gumbel distribution. We conduct a simulation study to compare maximum likelihood estimates and Bayesian estimates. In the third part, we investigate self-exciting point processes and we integrate a power-law covariate model to this intensity of this process. A maximum likelihood procedure for the model is proposed and the Bayesian approach is suggested. Lastly, we present an application on thunderstorm data collected in two French regions. We consider a strategy to define a thunderstorm as a temporal process associated with the charges in a particular location. Some selected thunderstorms are analyzed. We propose a reduced maximum likelihood procedure to estimate the parameters of the Hawkes process. Then we fit some thunderstorms to the power-law covariate self-exciting point process taking into account the associated charges. In conclusion, we give some perspectives for further work
Goodness-of-fit tests in reliability : Weibull distribution and imperfect maintenance models by Meryam Krit( )

1 edition published in 2014 in English and held by 2 WorldCat member libraries worldwide

This work deals with goodness-of-fit (GOF) tests in reliability for both non repairable and repairable systems. GOF tests are efficient techniques to check the relevance of a model for a given data set. For non repairable systems, the Exponential and Weibull distributions are the most used lifetimes distributions in reliability. A comprehensive comparison study of the GOF tests for the Exponential distribution is presented for complete and censored samples followed by recommendations about the use of the tests. The two-parameter Weibull distribution allows decreasing and increasing failure rates unlike the Exponential distribution that makes the assumption of a constant hazard rate. Yet, there exist less GOF tests in the literature for the Weibull distribution. A comprehensive review of the existing GOF tests is done and two new families of exact GOF tests are introduced. The first family is the likelihood based GOF tests and the second is the family of tests based on the Laplace transform. Theoretical asymptotic properties of some new tests statistics are established. A comprehensive comparison study of the GOF tests for the Weibull distribution is done. Recommendations about the most powerful tests are given depending on the characteristics of the tested data sets. For repairable systems, new GOF tests are developed for imperfect maintenance models when both corrective maintenance and deterministic preventive maintenance are performed. These tests are exact and can be applied to small data sets. Finally, illustrative applications to real data sets from industry are carried out for repairable and non repairable systems
Modélisation conjointe de trajectoire socioprofessionnelle individuelle et de la survie globale ou spécifique by Maryam Karimi( )

1 edition published in 2016 in English and held by 1 WorldCat member library worldwide

Being in low socioeconomic position is associated with increased mortality risk from various causes of death. Previous studies have already shown the importance of considering different dimensions of socioeconomic trajectories across the life-course. Analyses of professional trajectories constitute a crucial step in order to better understand the association between socio-economic position and mortality. The main challenge in measuring this association is then to decompose the respectiveshare of these factors in explaining the survival level of individuals. The complexity lies in the bidirectional causality underlying the observed associations:Are mortality differentials due to differences in the initial health conditions that are jointly influencing employment status and mortality, or the professional trajectory influences directly health conditions and then mortality?Standard methods do not consider the interdependence of changes in occupational status and the bidirectional causal effect underlying the observed association and that leads to substantial bias in estimating the causal link between professional trajectory and mortality. Therefore, it is necessary to propose statistical methods that consider simultaneously repeated measurements (careers) and survivalvariables. This study was motivated by the Cosmop-DADS database, which is a sample of the French salaried population.The first aim of this dissertation was to consider the whole professional trajectories and an accurate occupational classification, instead of using limitednumber of stages during life course and a simple occupational classification that has been considered previously. For this purpose, we defined time-dependent variables to capture different life course dimensions, namely critical period, accumulation model and social mobility model, and we highlighted the association between professional trajectories and cause-specific mortality using the definedvariables in a Cox proportional hazards model.The second aim was to incorporate the employment episodes in a longitudinal sub-model within the joint model framework to reduce the bias resulting from the inclusion of internal time-dependent covariates in the Cox model. We proposed a joint model for longitudinal nominal outcomes and competing risks data in a likelihood-based approach. In addition, we proposed an approach mimicking meta-analysis to address the calculation problems in joint models and large datasets, by extracting independent stratified samples from the large dataset, applying the joint model on each sample and then combining the results. In the same objective, that is fitting joint model on large-scale data, we propose a procedure based on the appeal of the Poisson regression model. This approach consist of finding representativetrajectories by means of clustering methods and then applying the joint model on these representative trajectories
Modélisation conjointe d'événements récurrents et d'un événement terminal : applications aux données de cancer by Yassin Mazroui( )

1 edition published in 2012 in French and held by 1 WorldCat member library worldwide

This work aimed to propose joint models for recurrent events and a dependent terminal event. We show how separate analyses of these events could lead to important biases. That is why it seems necessary to take into account the dependencies between events of interest. We choose to model these dependencies through random effects (or frailties) and work on the dependence structure. These random effects account for dependencies between events, inter-dependence recurrences and unobserved heterogeneity. We first have developed a joint frailty model for one type of recurrent events and a dependent terminal event with two independent random effects to take into account and distinguish the inter-recurrence dependence and between recurrent events and terminal event. This model was applied to follicular lymphoma patient's data where events of interest are relapses and death. The second proposed model is used to model jointly two types of recurrent events and a dependent terminal event by introducing two correlated random effects and two flexible parameters. This model is suitable for analysis of locoregional recurrences, metastatic recurrences and death for breast cancer patients. It confirms that the death is related to metastatic recurrence but not locoregional recurrence while both types of recurrences are related. However, these approaches do the assumption of proportional intensities conditionally on frailties, which we want to relax. In a third study, we propose to model potentially time-dependent regression coefficient using B-splines functions
Contributions méthodologiques à l'estimation de la survie nette : comparaison des estimateurs et tests des hypothèses du modèle du taux en excès by Coraline Danieli( )

1 edition published in 2014 in French and held by 1 WorldCat member library worldwide

Net survival is one of the most important indicators in cancer epidemiology. It is defined as the survival that would be observed if cancer were the only cause of death. This is the only one indicator allowing comparisons of cancer impact between countries or time periods because it is not influenced by death because of other causes. The first objective of this work was to compare the performance of several estimators of the net survival in a simulation study and then on real data in order to promote unbiased methods. Those methods are the non-parametric Pohar-Perme method and the parametric multivariable excess rate model. The latest one needs a model building strategy. The use of diagnostic procedures for model checking is an essential part of the modeling process. The second objective was to develop a tool box composed of diagnostic tools allowing to check hypothesis usually considered when constructing an excess mortality rate model, that is, the proportionality or not of the effect of covariates, their functional form and the link function. The third objective deals with the study of the impact of prognostic variables, such as stage at diagnosis, on conditional net survival, that is, on the dynamic of the excess hazard mortality after the diagnosis of colon cancer
Effets conjoints du vieillissement, de la maintenance et de l'hétérogénéité sur des systèmes réparables : modélisation, inférence et prise de décision by Léa Breniere( )

1 edition published in 2021 in French and held by 1 WorldCat member library worldwide

This thesis deals with reliability issues in connection with the modelling of the failure and maintenance process of repairable systems, using recurrent events. Generic virtual age models are extended by adding time-dependent covariates. These covariates take into account the observed heterogeneity between systems that are otherwise identical and independent. They can bring crucial information on the systems degradation level. We allow to use these models through two data simulation methods, as well as a parametric estimation procedure. This inferential method is numerically assessed in a thorough quality of estimation study. Then, the models are used to optimise the preventive maintenance dates along the systems' life according to the information brought by the covariates and the past repairs, allowing to reduce the maintenance costs. We go further by offering to optimise the inspections dates of the dynamic covariates. Finally, we study the implementation of multi-systems goodness-of-fit tests
 
Audience Level
0
Audience Level
1
  General Special  
Audience level: 0.00 (from 0.00 for Quelques r ... to 0.00 for Quelques r ...)

Languages